A conversation with the genetics professor at Cold Spring Harbor Laboratory.

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Michael Wigler: Michael Wigler.  Professor of genetics atrnCold Spring Harbor Lab.

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Question: What does your research consist of on a day-to-dayrnbasis?

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Michael Wigler: Our lab studies the genome of organisms andrnalso the genome of cancer cells. rnAnd we work on two kinds of problems: the evolution and outcome ofrncancers, and also on genetic disorders of a spontaneous sort, that is,rnnon-heritable genetic disorders. rnAnd those are two very—it sounds like two very different things, butrnthey’re related by our methodology, which is genomic analysis.

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What we do is called difference analysis, for example, ifrnwe’re looking at a cancer, we’ll want to see where that cancer has mutatedrnrelative to the genome of the person who gave rise to that cancer.  That’s differential genomicrnanalysis.  And it tells us wherernthe cancer has mutated.  And fromrnthe types of mutations, the number of mutations, we can infer a lot aboutrncancer etiology. 

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Question: Is biology becoming a more quantitative thanrnqualitative science?

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Michael Wigler: Well, biology has always been influencedrnstrongly by quantitative types. rnMany physicists in the late ‘30s, early ‘40s, ‘50s, came into biology,rnstrongly influenced it.  There wasrna period, I would say, from the time I was a graduate student in the mid-‘70srnuntil the mid- to late-‘90s, where it was not particularly quantitative, and that wasrnlargely because of the revolution in recombinant DNA.  So, really all you needed to be a good biologist was a goodrnsense of logic and a good imagination. rnAnd mathematical and statistical skills weren’t really that necessaryrnfor much of biology.  And I was inrnthat group actually.  I had studiedrnearlier on as a mathematician but I used almost none of those mathematicalrntools when doing biological research. rnOf course, the logic comes in handy, but the tools were not veryrnvaluable.  There was no place forrnthem because the kind of data that we were getting was very individual data andrnI actually had a rule of thumb. I actually disliked statistics early on in myrnlife and I felt that if I needed to do statistics to see what I was observing,rnthen I wasn’t really observing anything. 

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But that changed with the advent of the sequencing of thernhuman genome.  That changedrneverything.  And the development ofrnnew high throughput methods of extracting data, it forced biologists tornreconsider the value of statistics and mathematics in the analysis of theirrnsubject.  So, a number ofrnbiologists moved in that direction. rnNot a lot, but quite a number did. rnAnd I was one of those who moved in that direction.

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Question: How has the sequencing of the genome “changedrneverything”?

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Michael Wigler: You know, we are so close, historically, tornthat period, and the data that’s coming out of that effort is still beingrngenerated.  I think it’s very hardrnfor any of us to really judge the impact that it has had.  It was a huge revolution in terms ofrnthe kinds of experiments one can conceive of doing.  The only thing comparable in my lifetime was the recombinantrnDNA revolution which changed entirely the kinds of experiments people did.  

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Since sequencing methods are changing so fast, the cost ofrnsequencing has dropped enormously. rnAnd with each drop in the cost, it changes entirely how you think ofrnattacking the problem.  So, in arnfew years from now we’ll be in a position to have DNA sequence of a very highrnquality for a million people and know the medical history of these millionrnpeople.  And there’ll be—I don’trneven think our computers are yet to a stage where they will be able to handlerndata of that type and the kind of analysis tools that will be needed to analyzernthat haven’t been developed yet. rnSo, we’re in a really a strange point in the history of biology wherernthings are changing so rapidly, we can’t quite see the shape of the futurernyet. 

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Question: What has your research revealed about the geneticrncauses of cancer?

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Michael Wigler: Yeah. rnWell, the first observation was that there was a very strong correlationrnbetween the extent to which the genome in a cancer cell has changed and thernlethality of the cancer.  So that,rnif one’s looking at cancer and there’s lots of changes in the genome, thatrnpatient is less likely to survive than a patient whose genome has just begun tornevolve.  That was the first majorrnobservation. 

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There were a lot of particular details that emerged fromrnthose studies, that is, we found the locations of genes that are called uncArngenes and tumor suppressor genes. rnThe individual genes at these places, many of the changes are what werncall recurrent.  They happen overrnand over again in different people with the same cancer, and there are genes inrnthose regions that one can show functionally alter the capacity of the cancerrncell to grow, divide, or spread in the individual.  So this has been an engine also for the discovery of newrncancer genes. 

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We weren’t the first ones to do this.  People have been using these techniquesrnfor a while, including ourselves, for a period of 10 years or more.  Sometimes particular drugs that arerngiven to a patient are determined by whether that patient has a particular genernamplification in their cancer.  Thernmost well-known example of that is patients with amplification of the HER2rngene will likely respond to Herceptin. rnSo, our review has been that specific amplifications will correlate withrndrug sensitivity, we’re in the middle of exploring that, and we’ve also begunrnto look at single cells within cancer. rnSo that we can now actually look at the genome of an individual cellrnwithin the cancer and that’s giving us a much more detailed picture of how therncancer has evolved. 

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So, we think we’ll be able to identify, for example, the earliestrncells, the earliest mutations in a cancer that will tell us how the cancerrnbegan to grow in the first place. rnIt will also tell us what you might call the tribal, or populationrnstructure of the cancer, and that tells us about how the cancer is... how thernindividual cancer cells are interacting with each other, interacting with thernhost, and migrating through the cancer, and possibly migrating throughout thernpatient.  So that we think that byrnlooking at the individual cells of the cancer, we’ll be able to improvernclinical staging and drug treatment enormously.  But this is a long-term project.  This will take us five years, 10 years.

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Question: How might this research impact clinical cancerrntreatments?

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Michael Wigler: Well, I can give you two ways—there are manyrnways this research could impact the clinic.  I can give you two very concrete examples.  If a new drug is being tested in arnpopulation with a particular type of cancer, one might look for correlationsrnbetween response to the drug and the genome profile.  That could tell you which patients are likely to respond torna drug so that patients don’t have to take a drug that’s not going to benefitrnthem and don’t have to suffer the side effects of a drug that’s not going tornbenefit them.  And that willrnultimately lead to the design of better drugs.  

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A second way—and this next way is not quite sciencernfiction, but we’re looking a little bit into the future—when we can examinernthe genome of individual cells, and can do that cheaply, we can develop earlyrndetection tests for cancer that are based on blood.  So, it’s now being appreciated widely that even cancers thatrnperhaps have not yet metastasized release their cells into the bloodstream andrndo so in fairly large numbers so that you can collect cells from the blood andrnidentify them as a kind of cell that shouldn’t be in the blood.  But people haven’t yet been able tornlook at the genomes of these individual cells.  So, some of the methodology that we are developing willrnenable us to do that.  So you canrnimagine that at some time in the future, you can draw blood in the doctor’srnoffice and just like the doctors now do what’s called a blood count torndetermine how many white blood cells you have, whether it’s likely that you’verngot a fever, they’ll be able to sort out from the blood this small proportionrnof cells that might be being spun off by a cancer somewhere undetected in thernbody.  And by looking at the genomernof those cells, and possibly by also looking at the RNA that those cells arernmaking, I'll be able to say "This person has malignant bone cancer," and then yourncan look for that. 

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So, this technology can ultimately lead to early detectionrnfor cancer.

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Question: How did you become interested in autism?

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Michael Wigler: My personal interest in autism datesrnfrom when I was a child, and I had a friend whose brother was quiternstrange.  And when I was in medicalrnschool, I realized that he had autism. rnIt was actually Asperger’s. He was a very bright kid, never looked yournin the face, constantly was throwing his arms up like that as though he hadrnmade some great discovery; and knew everything about baseball statistics.And so it made an imprint on me at anrnearly age.And it’s sort of arnwonderful, it was sort of a wonderful thing to see this fellow who actuallyrngrew up to, I think he had a successful career as a disc jockey.  So, I was always interested in autismrnand because I come from a family that’s somewhat left-wing, always looking forrnways I can do something that is a benefit to society.  And it struck me that autism was not a disorder that wasrnstudied by the scientific community very deeply.  But in the worst cases, it was tragic for the families thatrnhad an autistic child. 

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So, I was motivated by both of those things to have anrninterest in autism.  And when wernbegan to study cancer, which was in the early 1980’s, I knew at the time theyrnwere studying cancer that the tools that we were developing could later bernapplied to genetic disorders.  Notrnthe kind of genetic disorders where you inherit something from your parents,rnbut the kind of genetic disorders that arise spontaneously because of mutationrnin the parent’s germ line. 

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An example of those kinds of mutations that everybody’srnfamiliar with is Down syndrome; or Trisomy 21 I guess is the clinicallyrncorrect way to refer to it.  Thesernare new mutations.  You don’trninherit it in the classical sense, but it was obvious to people who thoughtrnabout it that human genome is not static; it changes over time.  That’s how we evolve.  And most of those changes are notrngood.  They result in some disorderrnor another, but they’re hard to study. rnMost people who study genetic disorders study inherited kinds of geneticrndisorders.  I was interested in thernother kind of genetic disorders that result from new mutation.  And new mutations are what we studyrnwhen we look at cancers.  Whenrnwe’re comparing a cancer to the normal person’s genome, the cancers differ byrnnew mutation.  That’s calledrnsomatic mutation. 

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The same tools that find somatic mutation can find germ line mutations if you compare the child to the parents.  The incidence of autism being relatively high—and by and large, these children are so different from their parents—it seemed to me that it was likely, just a priori, that autism was the result of new mutation in the germ linernpossibly affecting many, many, many genes that result in the same end behavior,rnor similar end behaviors, and that was being ignored by the community. 

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So, when we had the tools to go look at this, we didrnso.  And so it was a combination ofrnopportunism because we had developed the tools, and intrinsic interest fromrnboth a social point of view, the social good, and also from a personal point ofrnview.  That is, I had a personalrninterest in how does the brain go from being what we would recognize asrnbelonging to a normal person to somebody who is, in wondrous ways, veryrndifferent from us.

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Question: What is autism?

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Michael Wigler: Well, there are a triad of behaviors thatrnare the earmarks of autism.  Therninclude difficulty in social interactions, delay in the development of speechrnand communication.  And those arerndistinguishable and repetitive behaviors, almost obsessive-like behaviors.  

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The recognition of this triad as a condition we call autismrnbegan only in the late ‘30s, and as the diagnostic criteria began to be morernwidely applied, more and more children were being called autistic.  And the definition, I think, I mean,rnwhen people now talk about autism spectrum disorders where a child has varyingrndegrees of these abnormalities.  Itrnis not, in fact, an extremely well-defined disorder.  It has sloppy boundaries to normal behavior.  We all know people that are awkwardrnsocially, there are many people who learn language late in life, and we all mayrnknow people that have stutters, or have obsessive behaviors, or even hangrnwringing.  So there is something ofrna continuum of all three of these things. rnThat’s not a condition whose boundaries are well-defined.  Yet, if you meet a child with autism,rnyou can generally say that there is something profoundly wrong here. 

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But it’s a hard disorder to define better than that.  And probably the reason it’s harder torndefine better than that is that the number of genes involved.  The number of underlying causes thatrncan create this triad is very great. rnFor example, the syndrome itself is enormously varied.  And if you have listened to somebodyrnwho studies autistic children—children with autism, you’ll frequently hear themrnsay that each child that they see is different than the next.  It’s not really a syndrome in the wayrnthat Down syndrome is a syndrome. rnThere are a variety of genetic disorders that are frequently—you canrnalmost tell that the children who have these disorders have the same underlyingrncause, because they’ll actually look alike.  It’s not just Down syndrome that has that property, Progeriarnhas that property.  There are arnnumber of childhood disorders wherernthe children who have these disorders actually look alike.  

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That’s not the case in autism.  Each child has—is sort of wonderfully different than thernnext child, so there’s a huge amount of variability.  And I think this has confounded the general public becausernit appears that the rate of autism has been going up so dramatically.  In fact, I think that’s mainly due tornincreased diagnosis.

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Question: What is the “unified theory of autism” that you’verndeveloped?

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Michael Wigler: The unified theory of autism attempts tornreconcile several observations. rnThe first observation is that having siblings with autism is more common thanrnone would expect if each incidence of autism was random.  So, if a child is born has autism, arnbrother is born, the chances that that brother has autism are much higher thanrna male born to another family. 

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And twins, identical twins have an extremely highrnconcordance.  Something likern90%.  There is no other cognitiverndisorder whose concordance among identical twins is as high. 

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So, those two facts tell you that there is a geneticrncomponent to autism.  However,rnthere are families that have autistic children and there are large families andrnonly one child will have autism. rnSo, the genetics would look to be complicated.  There’s an inherited component because siblings have a higherrnrate of concurrence, but there might also be a sporadic component.  So, the issue is how to reconcilernthat. 

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I think that prior to our serious involvement in thernfield, people assumed there was what was called this complex inheritedrnmodel.  That there are many genesrnthat may be in the wrong state in the parents that come into some combinationrnin the child, so the children of these parents have a higher chance of havingrnautism.  But it’s not a classicalrnMendelian pattern where half of your kids have it, or a quarter of your kids havernit.  Half will have it if it’s arndominant, a quarter if it’s recessive. rnThe pattern seems more complicated than that. 

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What we did was come in and say, well, you know, it could berna combination of both.  In somernfamilies, it is perhaps simple Mendelian and in other families it’s spontaneous.  And if you assume that there are arnlarge number of genes that can give you autism, then you could have a veryrnlarge proportion of autism being generated by spontaneous mutation.  But if the mutations don’t all haverncomplete, what’s called complete penetrance, that is, you can pass on thernmutation and the child can carry it and not show the disorder, then his or herrnchildren could then be at risk in a Mendelian way of inheriting that gene.

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So combining these two ideas that the sibling risks isrnreally a combination of simple Mendelian in some families with other familiesrnbeing spontaneous mutation unifies these two observations and does so in arncoherent model.  So, the coherentrnmodel is that humans are mutating, the rate of new mutation giving rise tornautism is perhaps on the order of 1 in 200 kids, and something like half ofrnthose kids actually don’t come down with a diagnosis, they mature, they getrnmarried, they have children and those children are then at risk from the carriers. 

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Now, one of the very important clues that is compatible withrnthis model is that the risk of autism is much higher in boys than inrngirls.  If the model, almost anyrnmodel would predict that whatever genetic abnormalities exist in the boy,rnthose abnormalities will exist in the girl.  So girls have something that makes them resistant.  So girls, in fact, could be naturalrncarriers of genes that in the boy would give the boy autism.  And that girl might grow up and be arnhealthy and desirable mate and have children and her children, particularly herrnmale offspring might be at high risk because they might inherit the gene thatrnshe safely carries.  That’s thernessence of unified theory.  It doesrnnot explain why autism, why boys are at higher risk than girls.  But it does suggest that you can haverntwo forms of genetic involvement; an inherited involvement from a carrierrnparent and also those rare mutations that destroy a gene in the germ line. 

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Now, I should say, and I really have to mention this, thatrnin the model we’re not saying that only women are carriers.  In fact, there’s well-known examplernthat’s been in the news of a male sperm donor who had something on the order ofrn20 male offspring and half of them had autism.  So, that’s clearly a case where the sperm donor, who I guessrnwas judged to be normal, probably maybe even brilliant or even genius, was arncarrier of a simple dominantly inherited Mendelian trait.

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Question: Why do older parents tend to have more autisticrnchildren?

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Michael Wigler: rnThe incidence of autism goes up with the age of the parent, and that’srnentirely consistent with the new mutation idea.  Because it’s already well established in males that thernnumber of point mutations found in the male’s offspring go up with the age ofrnthe father.  And there’s also arncorrelation with the age of the mother. rnSo, there may be a mild increase in the rate of autism in those culturesrnwhere having children is differed and delayed.  The magnitude of that effect is not going to explain thernoverwhelming explosion in the number of diagnoses, but there may be a mild increase in thernrate of autism due to that.  And the agerndependence on the parents is consistent with the new mutation hypothesis.

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Question: Do you believe that environmental factors such asrnvaccines increase the autism rate?

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Michael Wigler: Well, any genetic disorder is an interactionrnwith the environment.  So, I don’trnexclude environment.  I just don’trnsee yet any strong evidence for a particular environmental factor.  I think that one could do studies.  For example, one could go to third world countries and do a study and ask is the rate of autism there the same asrnit is in the developed countries. rnNo one has done a study, that I know of, of that type, but it certainlyrncould be done.  That would answerrnthat question. 

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But certainly anything to have to do with the development ofrnan organism has an environmental component to it, but you can only study thatrnwhen there’s some evidence which enables you to isolate that environmentalrncomponent.  I think the vaccinernstudies have been now largely discredited.  They took mercury out of the vaccines and the rates ofrnautism didn’t change.  And now ofrnthe 12 authors of the original paper that got some people very excited, I thinkrn11 of those 12 authors have now withdrawn their backing for that paper and thernmethods used in that paper are really in doubt.  

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So, I don’t take it as there being any evidence thatrnvaccines are such an environmental factor.  It’s unfortunate that at the age at which parents begin tornrecognize autism in their children often correlates with the age at which theyrnreceive vaccinations.  That’s anrnunfortunate thing. 

There is arnportion of autism, probably the majority of autism that you can detect it veryrnearly once the child is... almost after the child is born.  Many parents of autistic children sayrnthey could tell very early on that there was something wrong with theirrnchild.  There are about a quarterrnof the cases of autism where it looks like the child, in the parents’ opinion,rnhas been developing normally and then, to their mind, suddenly goes off course.  And I think at least five percent ofrncases, it’s been very well documented that actually, a child has begun to loserngains that they have made.  So,rnthere is this component that’s very tragic when a parent feels relieved thatrnthey’ve gotten through, and I think every parent who has a child suffers throughrnnightmares that, you know, hoping that their child will be healthy and they give birth to a healthy child and then at age two or three, the child suddenlyrnstops developing.  That’s a tragedyrnof horrendous proportions, and it’s natural for the parents of such children tornlook around for the possible causes; something external. 

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However, it should be borne in mind that our brainsrncontinuously are developing at that age, and it is well-known that there arerngenetic defects whose onsets can occur at almost any particular age.  For example, there is a class ofrndisorders that are called Storage Disorders where the child develops normally,rnbut because of the buildup of some compound due to the faulty metabolism ofrnsome essential thing that they eat every day, builds up to a point and thenrnbegins to poison the brain.  And inrnthese cases, the child will develop normally up to a certain age, and then willrnoften regress and sometimes will die. rnSo, the idea that you can’t have sudden onset of an illness when thernchild is two or three is just wrong. 

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If there were a clear environmental signal, for example,rnsonograms, or too much television, or vaccinations, that would be somethingrnthat one could study, but in the absence of evidence for that, you have to askrnyourself, well what should we be looking for?  Should it be the plastic in bottles?  And I don’t think we can do that in ourrnculture.  I don’t think we can lookrnfor these possible environmental insults. rnThere are just far too many. rnBut if you go to a place like Nepal, or Mongolia, or someplace whosernenvironment is completely different, they don’t have television, they stillrnhave grandmothers raising the children, they don’t get sonograms.  You could begin to tease out and dornwhat epidemiologists do.  They gornand do cultural comparisons.  So,rnfor example, cultural comparisons have told us the incidences of breast cancerrnin Japan is one-third the rate of the incidences of breast cancer in America,rnand when Japanese women grow up in America, their rate of breast cancer is thernsame is American women.  Okay.  You can say, the environment possiblyrnincluding culture in some way, because the rate, or the age on which yournundergo puberty is relevant to breast cancer.  Has a study like that been done for autism?  No.  That’s where you would start.  And none of that’s been done as far as I know.

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Question: What will be the impact of your research on autismrntreatment?

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Michael Wigler: Yes, well there are two ways in which ourrnwork could inform clinical treatment. rnIn the area of early diagnosis. rnIf there’s a child and it’s developing—it’s giving off developmentalrnclues there might be something wrong, if we had a list of the kind of geneticrnlesions we could screen for, we might be able to determine early on that thisrnchild is going to develop a form of autism.  And if it’s correct—most disorders are correctable to thernextent that they are correctable, are more correctable early than late, when wernknow how to correct or treat, we’ll be able to start that sooner.  So, early diagnosis is going to bernimportant for any disorder.  That’srnone way. 

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Another way is children with a particular genetic abnormality,rnthat is, those children who share genetic abnormality, may have one particularrnway of treating them that’s different than children who have a differentrnabnormality.  We will only learnrnabout that once we can separate these children according to their geneticrnabnormalities.  That’s going torntake many, many years. 

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The third way is that in some cases, we will be identifyingrngenes, who by their very nature, tell us this is a correctable, treatable,rnsyndrome.  For example, we find arngene that’s involved in metabolism. rnThis child is perhaps got really a storage disorder of some type, butrnaltering the diet in those cases might be able to treat the child.  But unfortunately, we don’t yet knowrnthe identities of the autism genes. rnWe have regions and there’s a huge effort underway.  I would say, in particular by doingrnvery exhaustive sequence comparisons of children to their parents, we willrnidentify the actual culprit genes. rnAnd that will take us two to four years.  And there may be, unfortunately, I’m estimating around 400rnsuch genes that each one of which can cause autism.  But when we have those genes, we see what they do; we canrnsee what pathways they are interacting with, some of those will suggestrnimmediately treatments that can be tested.  We will be able to make animal models and test drugs inrnanimals to correct these things. 

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So, in general, the way to understand a disorder is tornunderstand its causes and then address those causes.  In the case of autism, most people would agree, I think mostrnscientists would agree the causes are genetic, and we have a pathway torndiscover the genes.  So it will berneasier to diagnose, classify by diagnosis into behavioral and even drugrntreatments, and discover new drug treatments. 

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Question: What made you choose science as a career?

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Michael Wigler: Well, the first thing I remember wanting tornbe was a middleweight boxer.  Andrnthat was because I used to punch my older brother and he said, some day you’llrnbe middleweight champion.  That wasrnmy first ambition.  After that, Irndrifted to science.  I thinkrnbecause my father was a chemist and my mother had a great deal of respect forrnthe social utility of the mind.  Inrnthat period, which was the late ‘40s, following World War II, early ‘50s,rnpeople were very optimistic about the impact of technology on quality ofrnlife. 

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The life of an artist was generally considered to be one ofrnsuffering, and so my parents certainly didn’t wish that on me.  And those were my two choices.  It was either science or the arts.  We didn’t have any—my grandfather was arntailor, so anything involving the hands was out of the question.  One had to live the life of the mind,rnand there were really these two paths. rnI choose science, but toyed with writing when I was in high school andrncollege, ultimately settling on mathematics, which I really enormouslyrnenjoyed.  And actually began torndevelop a disdain for science because science depended on the empirical worldrnas a source for the imagination, whereas in mathematics, you didn’t have torndepend on the empirical world.  So,rnto me, I thought that mathematics was the highest enterprise of the mind. 

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But I wasn’t good enough at it and it was taking me out ofrncontact with humans, so I decided I had to do something socially useful, so Irnwent into medicine.  And that was arndisaster.  I really couldn’t dealrnwith the uncertainty of medicine, so I started doing research instead.  And that’s how I ended up being arnbiologist and molecular biologist. rnSo, I didn’t finish medical school, I went into microbial researchrninstead and came back much later in my life to utilize mathematics. 

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But in my case, it was entirely the influence of myrnparents.  They had admiration forrnthe life of the mind and they didn’t have admiration really for anythingrnelse.  I mean, I guess there mightrnhave been some athletes that they admired.  They admired people who had broken down culturalrnbarriers.  So, they had somernadmiration for people that struck down political archetypes, socialrnarchetypes.  But mainly they feltrnthat their kids should be active with their minds and do things that theyrnenjoyed based on their own imaginations, their own training.  So, I never questioned that. 

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Unfortunately, I didn’t realize what they had done.  So, when I had children—in case Ben and Josh find this—itrndidn’t occur to me that you actually had to imbue this.  I thought it would just be natural forrna child to want to be either a scientist or an artist.  And neither of my children had anrninterest in science.  And Irnrealized that when it was too late. rnSo, I missed out with my kids. 

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I think to get, if one has as a goal to have a society withrnmore scientists and engineers in it, then the culture has to respect people whorndo that.  And the way these peoplernare depicted in the cultural media is not generally positive.  There were in the ‘30s a number ofrnbooks that were written.  I don’trnremember their names, in which scientists of one type, Marie Curie, LouiernPasteur, were depicted in dramas as heroes.  But you don’t see that at all anymore.  Instead, scientists are villains,rnthey’re socially awkward, they’re not the kind of people you can cuddle up to. And I think that if popular culture does not reflect the value of science,rnpeople are not going to go into it. rnAnd America will be dependent on people coming in from the outside tornfulfill the positions of engineers and scientists.

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Question: Have you ever been completely surprised by thernoutcome of your research?

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Michael Wigler: Well, science is a very—it’s actually a veryrndifficult field because you need probably above everything else, extraordinaryrnpatience.  And what keeps you goingrnis discovery.  And sometimes in arnlifetime, you may have one outstanding discovery.  Einstein used to say that he was unusual in that he had hadrntwo.  But any one would have beenrnenough to have kept him going. rnMost scientists are not in that league, but we’ve all had at some scalernthings that we’re really very proud of if discover them.  Often, we are looking for them.  The idea that a lot of discovery isrnserendipitous and accidental is tremendously, tremendously overplayed.  I think it’s much more likely that onernsees something, almost in everyday life that puzzles you and you carry itrnaround with you for some period of time, and then you see some way ofrnconnecting to it.  You could sayrnour discoveries in autism as an example of that.  At a very early age, I was impressed by this child and laterrnsaw an opportunity and I struck when the opportunity was there to satisfy myrncuriosity.  So, most discovery isrnof that type. 

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Sometimes you see things that you can’t explain.  And I shouldn’t say sometimes, a lot ofrntimes you see things that you can’t explain.  And sometimes you come up with explanations that are reallyrnexciting.  And 99% of the time,rnthose are wrong and there’s really some trivial explanation of the thing that’srngotten you excited. 

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Early in my career I used to hate those things and I used tornsay, only a manic depressive would love living like this.  You see something that’s weird, yourncome up with some great encompassing idea that will explain it, it’s going tornchange how people think, and then the next day you realize that you were reallyrna dumbass.  Nowadays when thosernthings happen, I actually really enjoy them because there are so few real "Eureka!" momentsrnin one’s life that you have to almost have to enjoy the fake ones.  I mean, after all, the feeling isrnjust as good.  So, I’ve actuallyrngotten to enjoy those weird results that we can’t explain, come up withrnfanciful ideas, and then try to batter them.  And then you get double satisfaction because you end uprndestroying the idea and it’s satisfying to destroy the idea.  Almost as much fun to destroy an idearnas to create one.

Recorded April 12, 2010

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