7. Behavioral Genetics II

[MUSIC PLAYING] Stanford University. Something incredibly cool I just found out about yesterday, which, oh, I wish I had known about two days ago, but still, it's useful. You remember those Siberian foxes and that amazing thing? You breed them for tameness, purely on a behavioral trait, and come back 30 generations later, and they look like puppies. They have the short muzzles, and the big roundy eyes, and the cute ears, and they wag their tails and all of that, punchline there being, number one, evolution can move really fast. Number two in some interesting, mysterious way, if you are selecting for certain behavioral traits-- in this case, one where you like being around humans and are all cuddly with them-- what you're also going to select for are a whole bunch of traits that are associated with baby wolves in terms of physical appearance. Turns out, there's a flip side of this going on right now with what are known as metro dogs, which are dogs that live in the subway system in Moscow. And I don't know, but they live in there, and a whole deal was made out of the number of them which get on subways and know which stops they're going to. And there's an entire website devoted to metro dogs, which are in Russian, but it has lots of nice pictures. But what they're seeing there is that these are dogs who, essentially, have been feral and in feral packs for decades and decades. And what have they been being selected for? Being able to scrounge, being, in fact, quite scared of humans, a lot of the time staying far from them whenever possible because they are raiding garbage cans, who knows what. And what they're seeing in the metro dogs is about 30 generations into it now, their tails are looking more like the tails you see on wolves. Their muzzles are getting longer. Their coat patterns are beginning to get less fancy and distinctive from all the different strains of dogs. These guys are being selected for the exact same traits that went into being wolves. It's a really interesting demonstration. Again, these guys are not surviving because they've got a different-shaped tail. It's just part of the package. If you were going to have this canine-like thing and be selected for being scared of humans, functioning in packs, having a fairly aggressive temperament, you're going to wind up looking like a wolf after a while. Same deal, again, very rapidly. So unexpectedly, Russia turns out to be the motherland of all sorts of interesting things with puppies and puppies in the past and puppies in the future and all of that, so that's wonderful. OK. However, I don't have any pictures of them that I've brought today, but go to www.metrodog.edu and see what they have to say. OK, so picking up on Monday's lecture, I recognize Monday's lecture was probably the first one officially to be able to blow half of you guys out of the water because it was really tough material. Not only was it, as promised, yet another disciplinary jump, but it was the first wave at a lot of material that went by fairly fast, and a lot of it quite subtle. What are the things to focus on in there? What did we cover Monday that's critical? Behavior genetics as an overall approach is not doing the constructing an evolutionary story. Who's got the best story? We win. It's not molecular genetics looking at evolutionary change driven by actual mutations down at the molecular level. Instead, it's looking for patterns of behavior that go along with relatedness. What we saw was-- the most completely useless version was, well, here's a trait that runs in a family, and it runs in the family more the more related the individuals are-- completely useless, bringing in the first of the problems that we're going to have nonstop in the subject, ruling out different environments. We saw a number of the classic approaches they have, which is studying monozygotic versus dizygotic twins, studying adopted individuals, or studying the gold standard of identical twins separated at birth, adopted, and then brought back together again. And in each one of those cases, that's explaining some degree of the confusion, eliminating some of the environment, but over, and over, and over again, this problem of environments are sneaking in all sorts of interesting ways. Adoption is nonrandom in terms of where placement occurs. All sorts of stuff like that-- making it harder to tell. What we then transitioned to was dealing with the most interesting realm of environment, having influences, which is this whole world of prenatal environment and environmental effects there, one version of it being this whole new field, fetal origins of adult disease, the fact that early events-- fetal environmental events-- can have lifelong consequences, even multigenerational, as we saw. And people are understanding the nuts and bolts of how that might work, that epigenetic stuff. So we saw that as one-- a very subtle realm of environment slipping in. And we also saw examples where "environment" could be occurring within an hour of birth, and where environment is occurring despite seemingly like similar things, like the number of math classes you take-- environment being very critical. What we also saw, just to make life a whole lot messier and more complicated, was violating the rule we have all known since infancy, which is you get equal genetic input from each parent. The business about mitochondria coming from your mother-- the business about, as we saw, more subtle version-- the same equal input of genes, perhaps, but the regulatory control is much more coming from the mother by way of the transcription factors, all of that and the cytosol of the egg, sperm having nothing interesting going on from a cell biology level, the egg having all of this. And where you can even get something as nutty as inheritance of an acquired trait, Lamarckian evolution. OK, so that was plowing through all of that, and I'm fairly certain that reviewing the last two hours in these last three minutes has not put anybody back in the water who was blown out of the water. So go to sections-- this is difficult material, and it's going to get worse today. OK, this is hard material. Make sure you read the extended notes because there's a fighting chance that will be more coherent than the lecture. OK, so we got to the point last time around of seeing that, OK, prenatal effects-- the last thing we focused on was the actual nuts and bolts of it, epigenetics, all of that. Now we transition to what became the much more modern, exciting version of behavior genetics, unless you happen to have yourself hundreds of pairs of identical twins separated at birth, which is to go and actually find the gene, finally beginning to bring together-- to marry the classical behavior genetics approaches with molecular biology. And it was starting around the '80s or so that people began to be able to work in actual molecular techniques into this whole field, and it started off in a very primitive way and has gotten much better since then. The version that you can start off with is you know something about the trait, or as we're really saying here, you know something about that there are differences in the trait among different individuals, and now you go looking for the gene. How do you do that? The first classical way of doing that is that you actually have an observable difference in two individuals, in two populations, in two branches of the same family, a difference in an external manifestation of what's going on with genes, a difference in phenotype-- appearance, behavior, some such thing. And what you then do is you use that approach to try to then find genetic differences. You get a whole bunch of examples of folks with one version, a whole bunch of folks with another version, and you start looking for where the differences are. Slightly more constrained version, you don't actually have the phenotype. You are not looking at eye color. You are not looking at how wrinkly somebody's face is. You are not looking at behavioral traits. You're not looking at anything external. The next more focused step is now, you're looking at proteins, what some proteins do. Here is some enzyme that turns this into that, and there's two different ways the enzyme can do it or two different variants on it. And now, we've got this bunch of people where we take their blood and look, and they've got this variant. These guys have this version of how the protein goes about its business. Can we find the genetic difference? Next step down, next step more frustrating-- when you can't see external differences that you're tracking. There is no phenotypic difference that you've got to work with, where you don't know what the protein does, what its function is. Next, lower rent version is to look at the same protein that comes in slightly different sizes because that's usually a hint that there are different functions. The way the protein works is going to differ, and somewhere along the way there, you came up with one version by having some insertion, mutation, or deletion, or some such thing. You don't know what the protein does, and you certainly don't know what that does in terms of the individual's appearance, behavior phenotype, but at least you've got something to work with there. So what it is you are using as your starting point-- easiest external signs. Next is what would be called intermediate physiological endpoints. Intermediate-- it's something functional, but it's not functional like how the person functions. It's functional like how an individual protein functions. And then, if you're up the creek with that, at least hopefully going for differences in the size of the protein, the electrical charge of the protein. For non-chemistry types, how this version of the protein interacts with a water environment versus how that version-- you don't know what the protein does, but at least you've got something to work with. You got a difference. In all of these cases, the strategy is to then see what are the gene differences that go along with it? Primitive initial version would be as follows. You've got, for example-- in this case, you were trying to find the gene for some disease. And this is where the whole field started because it is a lot easier to go after a disease. Either you have it or you don't if you pick the right kind of awful disease, rather than going on a phenotype like television taste. That one's going to be a lot harder to find the gene for. The whole field started instead looking at extremes of really major league, you-got-it-or-you-don't-have-it diseases. So you've got this family that has this disease running in the family-- PKU, phenylketonuria, for example, or Huntington's disease, or cystic fibrosis. These were some of the first ones to go. And what you now do is you've got the big family, and what you want ideally is a big huge family where about half the people have the disease and half don't. And the initial way the whole approach would be done was you get blood samples from everybody there, and you start sifting through everybody's DNA, and you're looking for a stretch of DNA that everybody with a disease has in common and that none of the relatives without the disease have. And what you've got at that point is what would be called a genetic marker because doing it this way, you're just sifting through a haystack. You're just trying to pick up big, crude patterns. The difference that you wind up seeing between these two populations of relatives almost certainly-- in fact, as far as I know, never once with this approach had you just found the individual gene. You found a stretch of DNA that's got 10, 20, 30 genes in there. But somewhere in that stretch is the interesting one. So at least you have a genetic marker here. You know the genetic neighborhood where the difference occurs. So this was at one point cutting edge, a technique called RFLP, restriction fragment link polymorphisms. Do not write that down. And this technique was incredibly slick at some point early on, and it is not easily done because you are dumping 20,000 puzzle pieces over here and 20,000 there, and you're looking for the one difference between the two that's otherwise identical. It's that sort of task. Nonetheless, using that approach, people began to get disease markers where they got the stretch of DNA that contained a whole bunch of genes and who knows what else, but at least the candidate gene, the gene that was floating around that was responsible for this disease, was somewhere in the stretch of DNA. At that point, what would be done is a number of things. First is people would obsessively, obsessively check their statistics to see just how certain they are that this is the genetic marker for this disease because you were soon going to be advising people whether to terminate pregnancies based on genetic tests like those. This is an area where more stringent rules were imposed before you announce you think you know how the universe works with respect to this disease. Really, really major room for things going wrong in terms of it being then applied clinically, so first big demand would be you really have to be much more certain-- a much more demanding field than lots of others in biology. The next issue would be this bioethics problem, which is you've got somebody from one of these families who may or may not have the disease. This is a disease that doesn't get you until age whatever, and you're younger than that, and this immediately exploded this whole issue for the first time. Should people get tested if they have the genetic marker for that disease, if they are a candidate for it? And this opened up a whole world of confusion about this, where a key feature of these debates was the fact that you haven't gotten the gene. You've just gotten the candidate stretch of DNA, and there remains a very small statistical chance that you've got the wrong one. For a bunch of reasons, there is that possibility. So do you let somebody take a test? Can people tell the difference between a yes and no and a statistical probability? What do you do if it's a disease where the person has just spent their last 10 years watching their parents slowly die from it, and there's no cure for it, and it's absolutely horrible? Do you give them a test that is-- if the bad outcome is going to throw them off the top of a building with a high likelihood? Enormously complex bioethics issue. The third challenge, though, was to step up the science from just having the stretch of DNA with a bunch of genes in there to actually find the gene. And in the years since, the molecular biology has gotten much, much better at moving past finding a genetic marker, we are 99.9% certain that the gene that's relevant is somewhere in this stretch, to finding the actual gene and then being able to see what's the difference in it between them and them. What's the difference, down to base pairs? Where is the mutation? Where's the difference coming from? That's the world of sequencing genomes now. That's where the field is at. So that has been enormously powerful in terms of potentially finding one single gene. But everything that came through in the molecular lectures last week should be pointing out there's not a whole lot going on in there that revolves around one single gene at a time. So hold on to really horrible diseases. Yeah, one gene, single mutation, but most of what goes wrong, if you want to start understanding the genetics of psychiatric disorders, of diabetes, of early-- of late-onset dementias, things of that sort, it's not going to be just one gene. So the next huge advance in the field was being able to do searches like these for multiple genes. One thing that has been used is a technique called microarrays, gene microarrays. And they were basically invented here on campus by a guy over in the med school named Pat Brown, who is already very famous for having done this and I suspect has all sorts of interesting awards coming for him down the line. This spectacular technique-- you take what is now called a gene chip, and through techniques that are absolutely boggling and make me feel queasy, what you somehow manage to do is you get all the copies of RNA that could be made in a cell from this individual. If you are completely new to this and you've managed to get in this far without having to think about what RNA is, ignore it. This is just sort of a subtle detail for people who are interested in this. What you do is you get a copy of each type of RNA made in a cell. You force the cell basically to transcribe all of the genes it has. And then you get this little chip, and you basically glue the end of each one of these RNAs to it, and you will have a chip with 20,000 of these little things. And then you use probes which will allow you to see which versions of 20,000 of those genes are different in this individual from that individual. Total boggling, has forced an entire new world of trying to analyze data, this new field of informatics because you're not looking at one gene at a time. You're looking at patterns, and that becomes a lot harder. That becomes incredibly important because, again, it's all sorts of the interesting stuff where it's not going to be one gene. It's a dozen. It's 100. So that has been one challenging approach. Another is a technique called QTLs, quantitative trait lowside. What that basically is built around-- that if you have subtle enough of tests, you could figure out this is a complex trait that is modulated by two genes, or by three, or by 17. You can see all of this going in the direction from techniques that would let you know you're kind of in the neighborhood of a gene, to actually identifying a gene that differs between the two populations, to the much more useful realistic world of whole bunches of genes, networks going on at a time. So using these approaches, people have made lots of progress. The most recent version of that-- I mentioned the other day there, one type of mutation, a macro mutation, is this business about variants of major stretches of DNA copy length variance, where a whole stretch of DNA is duplicated twice or eleventy different times. Can you identify traits that are occurring because of differences in the number of copies? Yet another version of dealing with this whole hierarchical, multi-level business about gene regulation. OK, take home message from this is 20, 30 years ago when all of this started, you can start with a trait, and through increasingly fancier techniques, you could find the neighborhood of where the gene is that the different versions of the gene correspond to the different versions of the trait-- moving from patterns of that to the neighborhood of the genes to the actual gene to whole bunches of genes to macro differences there, that's one approach. The other approach of the field has been starting the other way. You've got a gene. You've got a gene, and thanks to researching it in flies, and worms, and rats, and all of that, you kind of have a sense of what the gene does, and you have a reasonable guess of what sort of traits might be relevant in a human, and now you run it the other way. You have two different versions of the gene, and you look for differences in behavior, or differences in protein function, or differences in the size of the protein. You start with the genetic knowledge. And for our purposes, where people are mostly looking is at behavioral end points. So what do you see with that? Lots of findings in recent years, and my feeling is this is one of the more interesting ways of doing this behavior genetics-- starting with basic research with animals. You've got some sense of what the gene does. How about it in people? Because there is variability. First example, and this has to do with a really interesting hormone that we will hear plenty about down the line, a hormone called vasopressin. And vasopressin in rodents I think I already discussed. Vasopressin in rodents has a receptor, the vasopressin receptor. And what we talked about the other week is depending on which version of this you have, if you happen to be a vole male, it will determine whether or not you were monogamous or polygamous. That's interesting. What was also interesting was that difference-- the two variants were not in the gene itself but in the promoter, and that winds up meaning that the promoter caused in one strain the gene to be expressed in different parts of the brain than in the other version of it. OK, so what we saw there was all sorts of hints from the animal world that vasopressin has stuff to do with social affiliation, things of that sort. So what do you now do if you want to apply this knowledge to humans? The first thing you need to ask is, well, do we know where the gene is in humans? And with modern sequencing in the human genome, you've got it, so you know where the gene is for the vasopressin receptor. And the next thing you have to ask is, does it come in two different flavors? Does it come in two different flavors, and do they differ in the same way as the ones people have studied endlessly in rodents? Yay. Yes, indeed, the receptor gene is exactly the same in everyone, but there's two different versions of the promoter-- the same exact story. So that's great. If you've gotten that far, now you start looking for what the differences are between people who have one variant versus the other. And you've got to do your homework. You got to match them for age, and gender, and number of cavities, and all sorts of stuff like that. And when you've got that under control, you go looking for behaviors. What's the limit of this? By definition, you're only looking where the light is shining already. You're only looking where you already have a sense that maybe you should be looking, unless you're totally crazy-obsessive and want to try to measure everything possible in people and look for a difference. In most of these studies, you kind of know where to look. That immediately means there's all sorts of areas you're not looking. Nonetheless, with this approach, people have gone looking in humans at these different variants on the vasopressin receptor gene, and you find some really interesting differences. One was a paper published a couple years ago in a very prestigious journal, which got picked up in the papers all over the universe, showing if you have the version of the promoter that you find in monogamous male voles, you as a human male are likely to have more stable relationships than if you have the other version of it. Whoa. That's pretty bizarre. That's pretty cool. Next thing, a study that just came out in that same prestigious journal a couple of weeks ago, and this is one we're showing, which, depending on which version you have, how good are you reading facial expressions in other people? Subtle differences in facial expressions-- then, there's a whole other world of approaching, evidence emerging that in families where autism runs majorly through the families, people are seeing mutations in genes related to vasopressin and the vasopressin receptor. So this is one really cool example of starting with that approach, and this is a gene whose variants have something to do with some pretty meaningful realms of human social connectiveness, variability stuff. Totally interesting. Another example-- this is a gene coding for a protein called BDNF, brain-derived neurotrophic factor. Doesn't really matter. The main point of BDNF is it prompts neurons into growing new processes. And it turns out, BDNF does something that ultimately is kind of a drag for you. In one part of the brain, the amygdala, which-- I think I've already mentioned the amygdala has a lot to do with fear and anxiety and that sort of thing, and we will come back to that. Don't panic. But the main thing is BDNF plays a role in causing individuals-- individual rats-- when they are highly stressed to make the neurons in the amygdala grow new connections, new processes. What are you doing? You are training that rat to be anxious. You are training that rat to be hyper-responsive to scary things. BDNF appears to play this role. So now, the next step in this sequence-- and you'll begin to see it's the same pattern over and over-- people then found, ah, there's a couple of different flavors of BDNF. There are a couple of different genetic variants. There's a couple of different ways in which BDNF pops up in rats or mice or whatever, differing by a base pair here, an amino acid there, where you then do your scutwork and show, OK, this BDNF works faster than that version of it or it works less but it lasts longer, or who knows what. You find a functional difference. There's a genetic difference. There's two different versions of it, and it actually makes a difference for how the protein functions. And this has all been studied in animals, and now you understand what it's doing in the amygdala of a rat, depending on which version you have. And then the exact same strategy-- go look at the BDNF gene in humans and ask, well, do you see the same difference? Are the same two flavors in humans popping up as in rodents? Yes, indeed. And then, the exact same approach again, looking for differences, and you know where to start looking. What has that literature been showing? The type of BDNF variant that you have in the exact same way that it maps in rodents maps onto your likelihood of an anxiety disorder, the levels of stress hormones in your bloodstream, the levels of metabolic activity in your amygdala, the same exact sort of finding. Next, a whole other world, which we will learn much more about down the line. This is obviously a quick survey of a whole bunch of different areas. All of these we will come back to big time later on in the course. Next area, this neurotransmitter, dopamine-- you will learn amazing amounts about dopamine. Dopamine, which works through a-- you guessed it-- dopamine receptor-- and in fact, there is a gazillion different types of dopamine receptors. And dopamine receptor number four, D4, the dopamine receptor four gene has something to do with a whole bunch of interesting traits in rodents. And it comes with variability in the rodent versions, different flavors, and humans have variability along similar lines. And dopamine-- what is dopamine involved in? Pleasure, and anticipation, and reward-seeking behavior. What two different versions of the dopamine type four, the D4 receptor gene, begin to map onto in humans? Levels of risk-taking behavior, levels of sensation seeking, levels of novelty craving. That's interesting. Another example, a gene called NPY-- a protein, a neurotransmitter called neuropeptide Y. Do not get overwhelmed by all of these. It's just the same pattern over and over. NPY, same deal again-- and two different human variants have something to do with differences in levels, again, of anxiety, of metabolic rates in the amygdala, all of that. And in this case, the NPY difference is quite interesting because it's one of those where the difference is not in the gene structure sequence. It's once again a difference in the promoter. OK, so what have we have in all of these? This is a really powerful approach. The first version that we heard, you've got a behavioral difference. You've got a phenotypic difference. You've got a difference in how two proteins function, or their size. Go looking for what's the genetic difference between those who have this trait and those who don't. This version, reverse engineering it, you start off with a gene that comes in different flavors. You got a sense of what it does from animal studies. Do you have the same variation in humans, and does it map onto behavior? So all of these are amazing. All of these, it has to be emphasized in a way that will come back to haunt us also big time-- all of these explain tiny percentages of the variability in the data. There is nothing remotely resembling a world in which if you have flavor vanilla of the D4 receptor versus if you have flavor chocolate-- if you have flavor vanilla, you are going to be hand gliding when you are in preschool. You're going to be totally sensation seeking. And if you have the other version, you're going to spend your entire life collecting stamps or who knows what. It's not that deterministic. No surprise with this gene stuff. No single gene is going to be particularly deterministic once you get outside the world of phenylketonuria and cystic fibrosis and such. They contribute some explanatory power. So on one hand, amazingly cool, seeing these genetic links to aspects of human behavior. On the other hand, they're not very big effects, and this is something we will come back to endlessly down the line. OK, so this is how the field has gone about more recently trying to find links between variation in genes or their promoters and variations in aspect of behavior, running it both ways. And what all of this is looking at, what is intrinsic in everything we've been talking about with this behavior genetics, is oh, my God, the cliche finally emerges. Nature and nurture, and gene and environment, and gene/environment interactions-- what is becoming increasingly clear in the field is there's a third leg to all of this. There's a third leg that could be extremely powerful and is going to be the basis for the chaos and complexity lectures down the line, which is chance, the role of random events, the role of chance in being a form that transcends what we would call environment and is certainly not genetics, a whole different world where that contributes. OK, where will we see chance playing out an important role in all of this? Brownian motion-- for those who don't have a techie background, I will describe it in the way that I understand it, which is flailing desperately. Brownian motion has to do with the fact that molecules oscillate and use an intrinsic movement, oscillation, of molecules. You take a whatever full of water filled with all sorts of things-- molecules, whatever-- and they're all going to be vibrating to a certain extent because of this Brownian motion. I suspect that was the most amazingly incorrect description of what Brownian motion is, but that's the point. That's the main point, simply that there is this oscillation, which is completely random. It is just an intrinsic feature of how the world of physics and Albert Einstein's mustache works. And so you've got this Brownian motion stuff going on. So where might that play out in terms of chance? So we got here a cell with our four powerhouses of the cell here. And on the right-- let's assume this is a genetically identical cell, and I just got tired of drawing it completely-- but the same four mitochondria. And what we see here first off is genetically, these mitochondria differ. One of them has a blue spot. One of them has a red sweater. Wait a second. Every single cell in your body was built out of the same genome when you started off life. Ah-ha. Back to that thing the other day. Mitochondria have their own DNA. Mitochondria are going about their own business of dividing in the cell, of replicating their-- replicating themselves now and then with a mutation. Within any given cell, the mitochondrial sequence of DNA is going to differ from one mitochondria to another because they've been separate organisms that are inside a cell going about their own evolution, their own mutations, their own whatever. What you then have-- what would be called a mosaic of different genetic profiles of the mitochondria within a cell. So that in and of itself is pretty interesting because this is a whole other world. This is not the DNA back in the nucleus, and this is not variability introduced by jumping genes or accessibility of transcription factors to genes, all that. This is-- meanwhile, outside the nucleus, there's this whole weirdo world of these mitochondria that are functioning all on their own, so the different mitochondria in the same cell will have different genetic makeups. So great. So these two cells are absolutely identical. Each of them have four mitochondria, and each of them have two red kinds, one blue kind, and one that gets nothing. So now that cell is going to go about splitting in two. And what happens is it splits. And in the process of splitting, what the fluid, the cytosol, the stuff inside where all the molecules-- including the mitochondria in the other organelles-- are found. And it splits, and there winds up being a very simple question. Which mitochondria wind up in which daughter cell? And what we've got here is in this case, a split like that. In this case, a split like that. Oh my god, why did that happen? Is that because there is a gene in this one that says when you form a new pair of cells, have blue and blank in one and two reds in the other? And this one is a completely different instruction manual for how you split cells. No, simple randomness of where the mitochondria were in the cell when they split. A totally random event. So what you see here is you start off with two cells that are genetically identical. And within one round of cell splitting, these genetically identical individuals are already genetically different. How come? Because of instructions or a blueprint? No. Simply because molecules, organelles, things like mitochondria just oscillating around. And along comes a split, and who is stuck on which side of the divide. So you've got variability that way. Intrinsic in that is another type of variability, which the second I mention it, you will be able to run with effortlessly, which is floating around in here also will be transcription factors, and splicing enzymes, and other enzymes. And along comes the split. And there is not the remotest chance that half of every single type of transcription factor is going to go each way, and half of every type of splicing enzyme, et cetera. It's going to be who's oscillating where and where the cells splits. So you wind up not only with different outcomes in terms of mitochondria and their genetic makeup, you're going to have different distributions of different types of transcription factors. All due to this random oscillatory stuff. So that's one big component where chance plays a role. And what the chaos complexity lectures are going to be very heavily about is just how important stuff like this is, how important it is in explaining what goes on, how important it is in explaining why, no matter how much you know about what every single molecule is having for lunch next Tuesday, there's still going to be a huge degree of unpredictability. All of that is to come. This is just beginning to establish the idea yes, nature, nurture, nature, nurture. Chance also is the third leg in there playing a large role. Whether chance is what's going on when you get a transposable event-- you remember at the point that neural stem cells are beginning to divide into neurons. That's when they juggle around their transposable genes most dramatically. Whether that is a completely random event as to where the copies land when they come back to Earth, I'm not sure if people know. But I suspect there's an element of chance in there also. So this is introducing that notion in there. So great. So now you've got all these caviats, which is environment is subtle and coming all over the place, and early experience, and epigenetic changes, and all the different ways you could find genes linked to behavior. And don't forget, variability also has something to do with chance. At the end of the day though, what all of the behavior genetic approach is going to come down to at the end is a single number. We have studied this trait with adoption techniques, with looking for genetic markers, with looking for copy length variance. We have studied this trait and the variability of it. And thanks to us studying for a gazillion years, we can now conclude that 53.5% percent of the variability in this trait is heritable. You come up with this number at the end. This trait has a 53% heritability. That's the number that winds up coming out. Scientists report that this or that trait has variability as 80% heritability. This is the number that always comes out at the end. What's the heritability? Ranging somewhere from 0% up to 100%. This is heritability. And this is absolutely critical. Because this is a truly influential number. The one that people come away with when they are being taught, Oh, this trait is genetic. Those who want to be quantitative will have been told, Whoa this trait has 80% heritability. It has 90% heritability, all of that. And it's the wrong interpretation. And what we're going to spend a bunch of time on now is looking at what heritability actually means. The heritability number-- because it is completely different from the everyday intuition about what it means. And what it's usually telling you is how unimportant genes are in the deterministic way rather than the other way around. OK. So what does everyone assume? What is heritability telling you? It is telling you how much do genes determine the average level of this trait. You have one version of a gene, and there's the other flavor. And they produce different average levels of some behavior or something at the end. What heritability is teaching you, if you've got this completely wrong notion, it's teaching you how much do genes have to do with the average level of that behavior, that trait, that whatever. That's not what heritability actually means. What heritability as a number is telling you is not what genes have to do with the average level of the trait, it's what genes have to do with the degree of variability around that average. This is a point where things immediately seem panicky and start getting very, very complicated, all of that. We will see it's not that bad. And it's not that bad in a very critical way. OK, simple first sense of getting at it. Here's two populations where you measure something or other. And these three individuals, they come in at nine, 10, 11. And these come in at one, 10, and 19, or whatever. What's going on here? You average them. They have the exact same average. What's the difference? There's a lot more variability around the average here than in this case. What's the wrong idea that people have that heritability means? It's telling you how much do genes determine the average here. That's not what it's doing. It's how much do genes determine how much variability there is. Initially, this seems like a very subtle point. And what's the big deal? Because at the end of the day, it's still talking about how important genes are. What we'll see now is it's actually a way of seeing how less deterministic genes are in lots of cases. So this heritability stuff, talking about variants. Here we have an example. We've got some plant. Some plant with some gene that comes in three different flavors. And you measure something or other about the plant. This is how much water it retains, or of the plant's IQ, or something like that. You're measuring some trait, and you're asking, Does it differ as a function of which version of this gene you have? So you do your study, and this is what you see. And you say, Whoa, OK. I went and looked at this plant in a rain forest, and we identified the genetic versions of it. And look-- very different. The gene that you have there, knowing that, gives you a lot of predictive power over what level of whatever it is that you're measuring this plant is. That's great. So you're going to get your doctorate out of that, and you get some publications. And it's great, and you finally stop being a student. And it's terrific. And meanwhile, some individual who shares like none of your genes in common on the other side of the planet, meanwhile there are some S-O-B who's studying the exact same plant in the middle of the Gobi Desert. You're sitting here in the Amazon studying this, and here's this individual doing the exact same kind of experiment, saying, Oh, here we have this unlikely plant that grows both in the Amazon and the Gobi Desert. But here we have this, and we're studying this here. And what am I studying? I'm studying those three variants. Those three variants of this gene. And I'm asking do they influence plant IQ? The same thing that you were asking over here. And that individual was doing their study, and they see that yes, indeed, the gene influences what version that you have. And here you had A, B, and C. And here's what they see when they measure plant IQ. And it looks like that. And what do they conclude? Whoa, look at that. Knowing what version of the gene you have gives me enormous predictive power in predicting what the plant IQ is going to be. And then catastrophically, tragically, the two of you meet each other and discover that you're both researching the same plant. And you look at your numbers, and your heart breaks at that point. Because you look at these, and what's going on here? What's going on? Let's translate this notion of heritability, and variance, and all of that. Let's translate it into a very simple question you can ask, translating all of this in English. You're interested in what this gene has to do with plant IQ. And you're allowed to find out one piece of information. You could know whether the plant has version A, B, or C, or you could know whether the plant is growing in the Amazon or the Gobi Desert. Which piece of information is going to give you more predictive power? And what you wind up seeing here is if you can either know this or the environment, you want to know what the environment is. The variability-- plant IQ could come in at 98, 100, 102, eight, 10, and 12. Far more of the variability in those six numbers is explained by what environment it's going on in rather than the genetic difference. That's what heritability is telling you. And in a study like this, it would tell you that the heritability number is actually quite low. Because the amount of variation due to this is far less explained by the gene type than whether it's the Amazon or the Gobi Desert. So that's a first pass at it. Why is this really important? For the following reason. You're a scientist, and you are trying to understand how A, B, and C influence plant IQ. And you come up with something nutty and stupid like saying, Well, I would like to be able to do field seasons in both the Amazon and the Gobi Desert. And your advisor will say, or all of your elders will say something like, No, you can't do that. Because that's just-- you're not controlling for environment. You're not studying it in only one controlled environment. You can't go to-- they're such different ecosystems, all of that. Pick one and go study it there. And what you do is you go study it there. And as a result of just studying it here, you come away thinking that virtually all of the variability is explained by genes. What have you just done? You explicitly have designed your experiment so that you can't detect the environmental role in determining that trait. What counts as setting up the experiment as the right way for people who think about this sort of thing, standard sort of approaches to experiment, what counts as doing a good job by definition, what you're doing is biasing towards thinking the genetic input is more important than it actually is. Because scientists don't decide to study this trait in two different places. You don't decide to do a study where you're looking at some trait in both rats and ocelots, or something. Look, pick one species. Maybe even pick just one gender. Pick one environment. Don't have your rats in one room where the air conditioning is going nonstop and the other room you're barbecuing stuff. Control for environment. And by definition, if you've done the nice, careful, responsible thing that a scientist's supposed to do doing this sort of thing, you control for environment. What have you just done? You have just removed your ability to see the role of environment. And you have just artificially inflated how important you think the genes are. OK, let's take a five minute break. We are going to look at this in a lot more detail. Do not freak out if this is not immediately intuitively obvious. Questions that just came up. The first one is pointing out one of those where I probably should have actually taught something clearer. What are you talking about with proteins being different sizes? How do you figure out proteins are different sizes? And the answer is you make them stand against the wall in their bedroom with a ruler, and you mark it there. And then you see if they differ in size. Or if that doesn't work, what you do is you use various biochemical techniques. You basically make something akin to a thick, homogeneous soup of something or other. And you put the two different versions of the protein in there, and essentially you sit and wait and see how far they sink down. And the one that's heavier is going to sink down further. Anyone who knowns about gels and the electrophoresis, that's insanely simplified. But that's basically the notion of it. Put them where they move through something as a function of their weight, gravity, and you could then pick up size differences. The other good question that was asked is, What did you just say in the last 10 minutes? This is very difficult. This is an extremely subtle point. And I'm going to hammer it in over, and over, again here, in sections, all of that. Why is it so important? Because number one, this is a number, heritability, that the general lay public comes away with interpreting incompletely wrongly. And number two, the vast majority of scientists, when they're working in this field of behavior genetics, design their experiments so that by definition, they are eliminating all sorts of realms of environmental influences. So going back to this here. So here we see once again this simple question. Use this one over and over translating all this theory in variation and stuff. Always translates into the same question. I can find out what type, what version of this gene, or I can find out which environment this is happening. Which one do I want to know if I want to be in a better position to guess what's going on? And when it looks like this, you don't want to know the genes. You want to know the environment because it's far more powerful. And if you only studied this in this setting, you would come away saying, Oh, this variability is entirely explained by which version of the gene. Oh, this trait, plant IQ, has 100% heritability. And what you see there is when you combine it together with numbers like these, it's 15% heritability. So that's totally critical to hammer in. So what are some of the responses at that point by people who will say, That's ridiculous. If you're saying what heritability mostly should be teaching us is how unpowerful genes are, what would be one of the initial responses? Great. How many plants out there are growing in both the Amazon and the Gobi Desert. And it's so hard to study IQ in plants. This is a totally artificial dichotomy between the extremes of environment. You're like inflating things now. You're cheating in the other direction to get the most dramatic artificial circumstances to inflate your sense of how important environment is. This is totally artificially dichotomized. So think about humans, and think about one single fact, which is we inhabit more different environments than any other species on Earth. We live in the Amazon, and we live in the Gobi Desert. And we live in Peoria, and we live in all these things. And we have more exposure to different sorts of environments. So immediately, that argument goes down the drain. OK. So now instead, somebody argues something different, saying OK, sometimes plants have IQ in the Amazon and in the Gobi Desert. And I get your point, your stupid point here that ooh, environment can make-- No one's going to argue that the difference between the Amazon and the Gobi Desert isn't important. Oh, yeah, OK. Well, humans, they live in both, all of that. It's not an artificial difference. But you notice something? Isn't it interesting that in these two different environments, C plants always have the highest IQ, and A plants always have the lowest. That's telling us something about that gene. That's telling us, and you're then saying well, yes, yes, it differs by environment. But we've just learned something very important about these gene versions. Which is, in totally different environments, version C gives you a higher plant IQ. So that's important. Yeah, yeah, environment. But we've just seen how powerful this gene is. But then you run into the person at the conference who is studying it in the Gobi desert, and they put their data up and it's even worse than in the last version because it looks like this. And what have you just learned? That you can't say a thing about this gene. You have just learned the translation of this sentence. The first critical sentence we've had over and over is, if you can only know one factoid, one about which gene version or what environment, choose the environment, we have now just learned a second sentence. A second question to ask. Which is, what does having A, B, or C have to do with plant IQ? And if the answer is "it depends," you've just seen this subtlety. If the answer is, "it depends on which environment you're looking at." if you're looking in the Amazon, C gets you the best plant IQ. if you're looking in the Gobi desert, C gets you the worst plant IQ. What have you just shown? What is technically the definition of a gene environment interaction? And we've just seen going from, well yeah, yeah, they're very different, but C is always the best. Isn't that interesting? To a completely different profile. What does A, B, or C have to do with plant IQ? It depends. It depends on the environment. That's how you've just defined, that's your diagnosis, for gene environment interaction. And what ultimately one has to argue is that it is impossible to ever say what a gene does. You can only say what a gene does in the environments which to date it has been studied in. OK, let's see that expanding even more. Because you've got this-- OK, let's jump ahead. OK, so this is showing you now just how totally nutty and counter-intuitive heritability terms actually are. You ask a question. What's the heritability of number of fingers on your hand? You know, genes have to do with the fact that we've got five fingers instead of flippers, or some such thing. Genes have huge amounts to do with it. You're not asking about the average number of fingers, you're asking about the variability. Remember that again. So what are the circumstances out there which will give somebody six fingers instead of five? That's incredibly rare. What about four fingers instead of five? Oh, industrial accidents. Three fingers instead of five? Lots of industrial accidents. Two? Change jobs or whatever. What are we seeing here in terms of, how much do genes have to do with having fewer than five fingers? It's all industrial accidents. Genes have nothing to do with it. There's no doubt some weirdo disease out there. But for our purposes, this is how it works. What have we just discovered? Number of fingers, that trait has a 0% heritability. That's totally bizarre. That's completely counter-intuitive. Genes have everything to do with why the average human has five fingers, but they have nothing to do with the variability. In that case, it's entirely environmental. The number of fingers you have has 0% heritability. Now let's look at another example. It's 1950 in Eisenhower America. Actually, it wasn't until 1952. But it's a very different world than now. And one of the things that you would never ever, ever, never, never, ever see in the United States would be some guy wearing an earring. Unless in a very cloistered part of the country he was a sensitive guy. But for most of America, this is not what men do. They do not wear earrings. And likewise, in most of America, if you were a good red-blooded American woman, you would not go outside without your earrings on. So now you've got to say OK, well what causes variability in earring wearing behavior? And it's entirely explained by whether you are female or male, which is a genetic trait. What we've just seen is, whether or not you wear earrings in 1952 has 100% heritability. Totally counter-intuitive. Think through this again and again and again, because this makes sense. When heritability is a number about this rather than this, you get a world where 0% heritability for your number of fingers and 100% heritability for whether you are wearing earrings at that time. Because once again, asking OK, I've got a choice in the matter. I can either know the entire genome of this individual, or I can know whether they are in a frat where they close their eyes and work with a wood saw every now and then. Which fact do I want to know? That's the one that will tell me what about the environment going on with them. Or now you have a choice. I can either know the entire genome of this person, or I can know that what sort of environment they're living in 1952. What do you want to know there is, male or female. If I know that, I can completely predict this behavior of earring wearing. So this totally counter-intuitive thing here, where heritability is telling just the opposite of what people intuitively think. And as soon as you deal with that and recognize that and recognize the way scientists do experiments, is to try to do things as cleanly as possible-- study it only in one place, in only one setting, only one circumstance-- you have just artificially guaranteed that you're going to come away more impressed with the genes than they actually deserve to be. So how would this look? Beginning now in more detail. So what we've got here are a number of different ways in which you can see when are genes important, when are environment important, that sort of thing. OK, so we have here two different traits-- no, we have one trait, two different flavors of a gene. Flavors A and B. And three different environments. So here you have the Amazon, the Gobi Desert, and a roller coaster. And you're measuring plant IQ. And there's two different versions of the gene there. And you're asking well, what does gene, what to environment have to do with it? Your data look like this. What does it tell you? Environment makes no difference at all. It doesn't matter if you are in the desert, the rainforest, whatever. Which version of the gene you have entirely explains variability. So this is what a heritability of like 100% would look like. Now you do the study, and instead you get data like these. You'll note just one of the most important things about being a card carrying scientist, which is data are plural. Which, talk about counter-intuitive, earrings are genetic and data are plural. So now you get these data and you see as follows. In this environment, no difference depending on what type of gene you have. In this environment, no difference, no difference. In each environment, very different averages. Ah, this is what it would look like with 0% heritability. There is no difference at all of the variation explained by gene variation. It's all environmental. So now we have a version that forces us to put in the same phrase we heard about before. This is what your data look like now. And you now ask the question, well, what does being in environment-- what does your environment have to do with your plant IQ? And the answer is, it depends on which version of the gene you have. And now you ask, what does having a certain version of the gene have to do with your plant IQ? And the answer is, it depends on which environment you're in. This is, in a sense, the verbal definition, again, of a gene environment interaction. What do genes have to do with this trait? Depends on the environment. What does environment have to do with a trait? It depends on the type of genes. This is what the data would look like. And here you have an interaction. And in some fudging of the numbers, this is what 50% heritability would look like. What we just saw here before, our hypothetical example of the messiest it could get, this is the one where the people come back and say, yes, yes, yes, environment matters. But you notice version C is always associated with the highest IQ. And here we have the version where depending on the setting, if you have this type of gene, it gets better. If you have this type of gene, it gets worse. This is one where there's a dramatic interaction between what the genes are doing and what the environment is doing. This is one that's going to have an even lower heritability because this is one where you are saying big time, it depends. It depends on what the gene type is. It depends. It depends on what the environment is. This is, in a sense, as dramatically as it could be that case. So you constantly have stuff like this going on. Let's look at an example where, in fact, you wind up seeing something like this. Back to our iconic mutation disease from the other day there, PKU. Phenylketonuria. Just to remind you, do not worry about the details. It's this disease where normally there's this thing in your body which would be toxic to your brain unless it's turned into something else. And this is the enzyme-- the protein, and thus coded for by a gene-- this is the enzyme that turns the scary version into the safe version. And in PKU, you have a mutation in this enzyme, it's not doing its job. The scary version builds up and wipes out your nervous system. That looks bad. And what we've got now is a trait where you're going to say, well, let's see. I am very interested in knowing, being able to predict whether or not this person has a fairly normal looking brain or whether it looks like Swiss cheese. Do I want to know whether or not they're growing up in Idaho versus Montana? Or do I want to know whether or not they've got a mutation in this enzyme? Obviously, you want to know if there's a mutation in the enzyme. Seemingly, heritability is 100%. But now you do something which people have been doing for people with PKU for a couple of decades now. Which is, you put little labels on bottles of food and stuff saying, if this food contains the scary bad news thing. And if you have PKU, if you simply don't eat food that contains that-- if you have what's called a fennel alanine free diet-- you don't get your brain looking like Swiss cheese. What have you got there? You've just put in an environmental influence that has reduced heritability down to zero. This is a case where we've got something like this looking. And here we're measuring is, like, the Swiss cheese index, or whatever of the brain. And what we've got here is, this is an environment where people know how much of the stuff there is in different types of food and don't eat it. A simple environmental-- not so simple-- but an environmental intervention. A behavioral change in the environment. And you've just reduced heritability from 100% to 0%. So that is a dramatic version. Now, let's look at a version of a real life example of this. This would be with-- I think I've already put this one up. OK, does this work familiar by now? No. OK, that was at Thanksgiving. OK. What we've got here is a gene that's got something to do with depression. It's a gene that has something to do with neurotransmitter serotonin. Details don't matter, they will come later. But the gene comes in two different flavors. And one version of it, based on everything that's known from laboratory animals, one version should be the kind that predisposes you more towards depression. So, in this incredibly important study that was done a number of years ago, a guy named Caspi, Duke University, and colleagues, they had been studying 17,000 people basically from birth up to age 25 or so in New Zealand. And who knows why in New Zealand, but studying them there, and following and asking. They took blood so they know the whole genetic profiles. And looking at, among other things, by age 25, does the person have major depression or not. Have they had an episode of depression. And now let's go look at which version of this gene they have. And what would everything predict from all the animal studies, which is you have the bad version of the gene and you're, as a human, going to have a higher chance of having a depression. That's not what the data looked like. Instead, it was one of those "it depends." It depends on the environment. What you saw was, it all depended on how many major childhood stressors there were. Loss of a parent, divorce, abuse, some such thing. And the absence of any of those, this was the rate of depression in the people having the good version. And throw in one childhood trauma, two of them, three of them, and the incidence is going up slightly. Now, you've got the bad version of the gene. And it puts you more at risk only in certain types of environments. So here we have a great gene environment interaction. That's something straight out of this one. You're saying well, what does this gene have to do with the risk of depression? And the answer is, it depends. It depends on what your childhood environment was like. But now, one additional detail showing that this is actually a case of this. One that just gets ignored whenever people talk about the study because it's cool, but it's actually not all that important. OK, so here's the people with the good version of the gene, but it makes this point though. You've got the good version, and they're down here. And you know what's going to happen, the bad version is going to be exactly the same. But you look at the data closely, and in the absence, the bad version is actually a little bit protective from depression versus the quote "good version." What have you just discovered there? It's one of these. This is a radical gene environment interaction. Not only is it the case that, does this put you more at risk? Well, that depends on the environment. Depending on your environment, it could put you less at risk. This one is not a big deal because there's a tiny difference. There's no reason to pay attention to it, other than just sort of pointing it out pedagogically. But this is an amazing example where this can go in the opposite direction. This is a hugely important gene environment interaction. So what all of this begins to set you up for is, you've forgot this heritability number. And people come away constantly thinking about, it's telling you about how much the average level of a trait is determined by genes. It's instead telling you how much the variability. What that means, thus, by definition, that there's all sorts of nutty counter-intuitive things going on, where earrings are totally heritable and number of fingers are not. What that tells you is, by definition, the way experiments are set up to make things nice and clean and interpretable, scientists typically remove environmental variability. Scientists typically artificially have boosted up the seeming heritability of a trait. What does that tell you? The more different environments you study a trait in, the lower the heritability is going to be. Because you are going to be getting more and more opportunities for things to be different. More opportunities to be able to say, it depends. It depends on which environment. We've just studied it in 99 different environments, and it always looks like this. No difference by environment, and genes always make a huge difference. And then you go out and, before dying of fatigue, you study it in the hundredth environment, and it now looks like this sort of thing. What you've just learned is, this is a "it depends" example. And the more environments you study something in, the lower heritability is going to be. Translating that into English, the more environments you study a genetically influenced trait, the less interesting and important the genes are going to be. The less interesting and important they're going to be in answering, what does this gene have to do with whatever? And what we're seeing over and over again is, the only way to answer it over and over again is, it's going to be an "it depends." It depends on the environment. Ultimately-- as I said a little while ago-- ultimately, it winds up being meaningless to ask what a gene does. Ultimately, the only really truly scientific way you can answer a question like that is, what does this gene do in this particular environment? People make this big deal out of oh, genes do something, environments do something. And every now and then, hooray, they interact in some exciting way in teaching the gene environment interaction cliche, that's what's happening every single time. And that winds up being the basis of that quote from Paul Ehrlich in this department that I put on the handout, which is great, summarizes this entire point, asking whether genes or environment have more to do with some trait is akin to asking whether height or length have more to do with the volume of a rectangle. They're inseparable. There is no such thing as a gene influence outside the context of an environmental interaction. OK. Let's look more at what this looks like. Here, this being one great example. And this being this iconic one. And this is a finding that is destined to be, like, the most important in the last quarter century in biological psychiatry. It is the most powerful demonstration in the realm of abnormal human behavior of what your genotype has to do with your behavior. The most amazing, logical, intuitively reasonable demonstration of "it depends." It depends on how stressful the childhood environment was. Really great. Bringing things back to last weeks sort of molecular lectures, people already know who study this. The two different versions of the gene, certain classes of stress hormones interact with the two versions differently. When stress hormone levels aren't particularly raised, that difference isn't being manifested. The more of a history of stress-- and it's obviously more mechanical, more complicated than just how much you're exposed to-- but the promoters, the variation here is in the promoters. The promoters interact differently with those glucocorticoid stress hormones. In the absence of the glucocorticoid stress hormones, because in the absence of something exciting, your genetic difference makes no difference. So we've just translated an epidemiological answer-- what does this gene have to do with depression? It depends. It depends on your childhood stress history. We've just translated that into last week's molecular biology, what does this genetic variance have to do with whether or not you have depression? It depends. It depends on how much childhood exposure to glucocorticoids you had. So we've just leaped from analyzing this in the context of this field, to translating that into last week. And translating that into the endocrine lectures that are going to come next week, beginning to show, OK, you're an epidemiologist. The answer is, what sort of environment? You're an endocrinologist. The answer is, well, the hormonal environment. Whether you define it, it's the same punch line. It depends. It depends on the environment. So this is the best, most amazing example of this in all of psychiatry. Except, these guys-- Caspian colleagues-- measured something else and they got just as bestest of an answer for that. Which is, they looked at another gene that has variation. One we will hear about down the line. A gene called MAO, monoamine oxidase. All we need to know right now is, a gazillion animal studies suggest that one version of the gene predisposes more towards aggression than the other. Whoa. So they've got 17,000 people who've just had 25 years worth of opportunity to be aggressive or not, and they got the genes. And now they ask the question, rather than at age 25, has this person ever had a major clinical depression? Now they ask, at age 25, has this person ever been in trouble with the law for some sort of antisocial behavior? Antisocial behavior is the new jargon for what used to be called sociopathic behavior. Has this person been in trouble with the law for sociopathic behavior, anti-social. And does it vary depending on which version of the MAO gene you have? And what you get is, not only is the answer "it depends," the graph is basically identical to this one. It's superimposable, the magnitude of the effect. What was this in that case? Whether or not you had, and how severe your child history was, of abuse. The more childhood abuse you had, the more having the wrong version of the gene increased your odds of having anti-social aggressive behavior. Once again, a major dramatic "it depends." And it's stunning. You look at these two different papers, both were published in "Science" a couple years apart. Landmark studies, all of that. And the two graphs really are virtually superimposable. The same magnitude of effects. The same answer. It depends on your childhood. So that is a very strong example. Next one, another one, now you go back to this gene difference with the serotonin, the depression world. And now you study it in monkeys and the variation there, there is a variation in brain chemistry related to depression, all of that depending on how stressful the monkey's childhood was. Same exact sort of finding. What else? Now when you begin to look at-- going back to that world of dopamine receptors and thrill seeking and all of that-- and what you look at there is variability in a certain type of different dopamine receptor gene. And what you find there is, if you have a certain version of that gene, you have less social attachment. There's a whole psychology of how you measure that. And God knows why. It's associated with less social attachment if, and only if, you got brought up by a mother who was cold and withdrawn. There is once again a "it depends." My looking at that, it's nowhere near as clean as this. But it's the same sort of theme again. Another example of it. There's another gene called FAD2. And don't even ask me what it stands for. But which version of the gene you have has some predictability over your IQ. That's kind of interesting. It's not a big effect, but nonetheless it is demonstrable. Which version of the gene you have has some control, but there's a "it depends." Which version of that gene you have has something to do with IQ if and only if something. Let me tell you what this FAD2 is involved in. It is involved in carbohydrate metabolism. Carbohydrates-- carbs, carbohydrate metabolism-- it codes for some enzyme that breaks down carbohydrates and no doubt, some certain kind. OK. What's going on here? You've got two different versions of a gene that break down carbohydrates, and you've got one version. And on the average, you'll have a higher IQ if and only if some environmental thing was happening. Any guesses what that environmental thing might be? High carbohydrate diet. High carbohydrate diet, OK. That makes tons of sense, yes indeed. That winds up being relevant. Remember, you're now-- not remember, because I didn't say it already-- but you're looking at IQ in kids. So you're looking now at carbohydrate stuff going on early in life. So frame it in that context. So, we've got a start of an answer here. So what else could be happening? If and only if the version you have of this gene that's involved in breaking down carbohydrates, translating into how you're dealing with the amount of carbohydrates in your diet, gets you a different IQ with an if and only if. What would the if and only if be? Build on that comment there. What else could it be? OK, I'm not even going to look. Somebody shout out an answer. [INAUDIBLE] You're right! OK, Who started? Somebody started saying something. Who started saying something? OK. Any other ideas? Breast feeding. Who said that? Look at that, they start pointing. The person doesn't even fess up. Who said that? It's in your notes. You're right. [LAUGHTER] OK. You want to be that way. I'm out of here. OK. So if and only if you read the damn notes, as it turns out. Yes! Breastfeeding. OK. If and only if you were having a particular type of diet very early in life that is extremely rich in the types of carbohydrates that this enzyme works on. So a very dramatic if and only if there. I don't know why I write that stuff. I don't know why I show up here. I should be doing one or the other and some sort of environment interaction thing. So yeah, breastfeeding. OK. So one more example, a very interesting one. And this is one that has at some point or other, I'd bet, been pertinent to every single person in this room. Which is, there's another genetic difference that has something to do with a certain cognitive aptitude. And this one everybody knows about. And this one is as follows. If you have-- there's two different versions of this sort of genetic picture and they're associated with different levels of aptitude in this particular cognitive realm-- this is not a world any more of one single gene at a time. FAD2, any of these. This instead is talking about a whole bunch of genes. If you have a Y chromosome or not. If you are male or female. A genetic trait. And what is the thing that has been demonstrated most consistently in the literature forever and ever and ever in terms of a gender difference in a cognitive skill in math performance. That has come through endlessly. I've already talked about it the other week. A small difference in the average median performance on junior high school old Johns Hopkins superstar kids taking the SATs. But a big difference in the tail at the end, high performance, all of that. This comes up in endless, endless studies. This comes up with kids at fairly young ages. There is this gender difference on the average-- yes, we're saying on the average, don't forget, you say on the average before you even ignore that-- you say on the average, boys are better at math than girls. Men are better at math than women. Male plants in the Gobi desert are better in math than female plants there. And so we've got a genetic trait here being a function of whether or not you get a Y chromosome. But then, a few years ago there was an astonishingly important paper published in "Science." And what these people did was look at math performance scores-- of I think it was 480,000 different high school kids. And all over the world. They didn't just study it in America. They studied it in 40 different countries. And they asked a very simple question. Which is, are there big differences in gender quality of life issues in this country? And there is a whole index that comes out of the World Health UN something or other called a gender equality index. Which takes into account, like, if there is-- and if there is, how dramatic of-- a gender difference in educational opportunities, in freedom of movement, in freedom to serve in an elected office, and freedom to vote, in freedom to choose who you're married to, and obviously the enormous variability on this planet in terms of that. And what they showed was, the greater the inadequacies, the greater the difference in gender treatment in the society across 40 different countries, the bigger the difference there was in math scores. It's not a function of gender, it's which society you're growing up with your gender. What was at the most extreme? Let me make sure I get the countries right here. Who had the worst profiles of the 40 countries in terms of the biggest gender differences in these quality of life measures? Turkey, Tunisia, and South Korea. Where was the United States? Sitting somewhere around the middle with most Western European countries. And which were the countries on earth which, as a block, had the lowest degree of different treatment of people in their society based on gender? The ever handy wonderful Utopian Scandinavians. So in comes the Scandinavians. And what you show is, by the time you look at the country on Earth that has the least gender differentiation of any, which is Iceland, you notice something different. There still is a gender difference. In Iceland, girls are better at math than boys, slightly. A small difference going on there. But nonetheless, as you go from the countries in which from day one, girls transitioning into women are given the most constraints of freedom of life, that's where you're going to see the biggest math difference scores. And you look at less and less of those sort of inequities. And the gender difference in the math score, by the time it's at the Scandinavian countries, it's down to zero. And then you get to Iceland, and it actually reverses. It's got nothing to do with your Y chromosome. We immediately come back to the first of those questions from before, that diagnostic question. You've got a choice. You want to have a sense of, in this population-- nah, even at the individual level. You've got a choice. You're comparing two individuals, and you want to guess which one is better at math than the other. You can either know their gender, or you could know whether they grew up in Tunisia or Iceland. Which fact do you want to know? You want to know about environment. Environment is vastly more powerful there. Another feature of that that has been interesting. So you then say OK, the extremes. OK, so in some societies, the means are exactly the same. But what about that difference way out at the highest level of performance. As I mentioned the other day, in the mid-1980s, looking at the highest first percentile of math performance on junior high school kids with their SATs, and there was a 13:1 ratio of males to females in there. When it was last studied a few years ago, it's down to a 3:1 ratio. Oh, that's obviously due to evolution over the last 20 years, because it's got to be due to genes. That's like saying genes explain the fact that in 1980s people, like, wore pads on their shoulders and, like, power sneakers to work or whatever. And the fact that nobody does that anymore shows that the gene for wearing that on your woman executive decor deal has evolved. That's asinine. You do not go from 13:1 to 3:1 with a trait in 20 years in a highly interbreeding mixed population-- in other words, humans-- and have this as a genetic trait. Even function at the extreme has squat to do with the genetics of gender. It's, I want to know what society the person got raised in. I could care less what their chromosome is. If I want to know how good they're likely to be at math compared to the other person, tell me where they grew up. That's the most important thing to know. Interesting additional thing. The second most reliable finding in all of measures of cognitive aptitude thing that has a gender difference is, on the average, girls being better at verbal performance tasks than boys. Women than men, all that sort of thing. So what's going on in those 40 different countries there? What you wind up seeing is, it depends on which country you're in. It depends on that gender equality index. And what you see is, in the worst countries there, by these measures, Tunisia-- who else was it?-- Tunisia, Turkey, and South Korea, what you see is, yeah, women get better scores on verbal tests than men. And as you go to the more equal places, the gender difference increases. In other words, you've got one of these. The more gender equal a society is, the less of a sex difference there is in math capabilities and the bigger the advantage is for females over males in verbal performance. It's got everything to do with what society you're in. This gender difference in this realm of cognitive skills means next to nothing. And if I had any technological skills-- I kept saying I was going to bring the figure from this paper, I'll have it posted-- because this one figure, it's across all these-- you just look at it and there's the answer. It's got nothing to do with the genetics of gender difference. OK, so what else would one want to emphasize here? OK, what else would one want to emphasize here? Which is, this is a total mess and totally complicated. OK what have we gotten to so far in this field of behavior genetics? There's all these different ancient ways of inferring something. Twins, adoption, there's the much more modern way, which is finding the actual genes. That's wonderful. That's exciting. Nonetheless, over and over and over, an environment gets understudied. Environment is far more subtle than you think. Environment starts earlier in life than you think. And when you do it in a very formal quantitative way, analyzing what genetic influences are about, you discover that scientists study things under circumstances where you constantly underestimate the importance of environment. Blah, blah, etc., etc. But at the end of the day, don't genes have something to do with something or other going on with this? And obviously, obviously they have some very important roles. You have genes that completely determine aspects of behavior. Single genes that completely determine your intelligence if you are a housefly. Lots of interesting studies there showing single gene determination, a lot of these behaviors. And it doesn't matter sort of what the economic opportunities are for houseflies in that country versus humans. What you see there is yeah, there are realms of behavioral biology where genes play very, very strong roles. And we will certainly see some of them in the lectures to come. But with two qualifiers. The first one we heard the other day. Which is, even when, with all of these criticisms on board and you've got every critical tool to slice up anybody arguing that here's a high heritability important genetic component, blah, blah, etc. You've completely cut it to pieces, and there still is a gene that seems to be doing something important for trait X. What we heard about the other day is, nonetheless, think about if there is an indirect genetic route for getting there. Is there a gene for extroversion? Or is there a gene for your height and how people of your height are treated? Is there a gene for picking at grubs? Or is there a gene for if you're really tall, you pick at grubs and people don't make fun of you. Is all of that business about indirect genetic effects? So even when you see a gene for something, you have to begin to ask to make sure that you are not, in fact, looking at an indirect effect. Final qualifier. When you look at the really interesting genes in terms of what they do. When you look at some of the ones that have the most to do, say, with what differentiates our genome from the chimp genome. When you look at things like juggling your DNA just when you're making new neurons, what you see over and over is, what human genes are about most dramatically is coding for ways in which you have freedom from the effects of genetics. And that is going to be a theme endlessly in the lectures to come. OK. For more, please visit us at stanford.edu.

Channel: Stanford

Views: 368,096

Rating: 4.8910341 out of 5

Keywords: Science, Interdisciplinary, Bioengineering, Genetic, Sociobiology, Darwin, Evolution, Sexual, Species, Natural Selection, Genetically Based Traits, Environment, Heritability, Reproduce, Reproduction, Survive, Gene, Variability, Mutation, Trait, DNA, Protei

Id: RG5fN6KrDJE

Length: 92min 44sec (5564 seconds)

Published: Tue Feb 01 2011