Dr. Armin Raznahan — Genes, Brain Structure, and Neuropsychiatric Disorders

Anybody who observes a person with a neurological illness like Tourette syndrome or schizophrenia can clearly see how these conditions affect behavior. What’s much more difficult to determine is how these ailments relate to changes in the brain. Dr. Armin Raznahan is a child psychiatrist who uses a genetics-first approach and state-of-the-art neuroimaging tools to examine how the size and shape of the brain differ in children and adolescents with neuropsychiatric disorders compared to healthy individuals. His discoveries about these illnesses could ultimately improve our ability to identify and treat people who have them, as well as predict which children might develop them.

Armin Raznahan, M.D., Ph.D., is a Lasker Clinical Research Scholar in the Human Genetics Branch at the NIH’s National Institute of Mental Health (NIMH). Learn more about Dr. Raznahan and his research at https://irp.nih.gov/pi/armin-raznahan


>> I am a big fan of early 90s electronic music from Detroit.

>> Who's your favorite artist?

>> Jeff Mills would be probably my favorite.

>> Okay, so what attracts you to that kind of music?

>> Funny enough, I had the opportunity to interview him because my sister's in that sort of scene, and had this interesting conversation with him that, about creativity, and he was talking about it from the side of making electronic music. I sort of tried to bring something out that might not have been there before. And I only realized in talking with him about it that there's a little bit of that in sort of science, too. So I guess I like the fact that there's a blank page, if you like, or an empty space, and electronic instruments that you sort of fill it in any way that's only limited by your mind. So that's what I like about it, the creativity.

>> Yeah, that makes a lot of sense.

>> And the beat.

>> Yeah, it's fun! And you have, as a scientist, you kind of have freedom to figure out facts about reality that could go in any direction, I suppose?

>> Yeah.

>> And so for non-scientists out there listening, what is it that you do?

>> So I'm a child psychiatrist, and I'm interested in understanding developmental disorders of the brain, and in trying to understand that, we're also really interested in understanding brain development and health, so we have kind of two lines of work. We try to map patterns of brain development in humans in health and use that as a framework to understand how atypical development may be happening in neurodevelopmental disorders. So I'm thinking of, when I'm saying neurodevelopmental disorders, I'm thinking of a kind of family of conditions that are currently called things like autism spectrum disorder, attention deficit hyperactivity disorder, intellectual disability. So we use these behavioral descriptions to sort of group people according to whether or not they look like they have one of these diagnoses. But we are trying to sort of understand these conditions in a slightly different way.

>> And maybe you already said that, but so what is the different approach that you're taking to understand these conditions?

>> Yeah, so it's interesting because for the--since we've had better tools for measuring the brain over the past sort of 20, 30 years, and there's been lots of work trying to find biomarkers for these conditions. So is there--like in bodily medicine, there are tests, and you can determine objectively whether someone has high blood pressure or not, for example, but we've not really had tests for psychiatric conditions. So people have been working quite hard to say is there a biological signature or biomarker that consistently accompanies the presence of autism or ADHD or some types of children in those conditions that would respond differently to treatment? And it's not been very productive, even though loads of money has sort of been invested in it. And it was a little bit of a mystery as to why it was proving so hard. People had lots of ideas, but what's become clear in recent years, the real message has come to us from genetics. So as our ability to measure genetic variation has immensely improved, it's become clear just how kind of complex and heterogeneous each of these diagnostic categories is. So it seems that one of the reasons why it's been hard for us to find, say, biomarkers for autism is autism is really the autisms, and often overlaps with other conditions. So what we're trying to do is to understand risk for neurodevelopmental disorders, but do it in a way that doesn't start with the diagnoses we've traditionally used. And we sort of, we take a genetics-first approach. So to understand these complex behavioral conditions, we don't group children according to how they're behaving, but we define groups of people who carry known genetic variants that put them at higher risk for developmental disorders. So we're actually starting with a biologically defined beginning, and then we try and understand how does that high-impact genetic variant actually lead to these neurodevelopmental presentations like autism?

>> Yeah, because there could probably be multiple outcomes of any genetic variation, so it kind of makes sense to start that way. And you can compare the different outcomes.

>> Absolutely. So it's, it goes two ways, but any one of these behavioral groups can be arrived at through hundreds of different high-impact variants. But exactly as you say, you take any one of these variants, and what we observe is there's a huge diversity in where children who carry these variants can end up, so exactly as you say, if we start off with a group of children--for example, we just finished recruiting a group of young people with extra Y chromosomes – males carrying an extra Y – and what's been remarkable is just the diversity in the sorts of presentations you can have. So we have young people and their families, incredibly generous research participants, travel to the NIH. It's a very intense process. They're here for sort of two days and undergo a series of questionnaires, interviews, brain scans, so we call this like a deep phenotyping study. We gather as much information as we can on the young person and their family, and then we use sort of computer approaches to model that big data and try and find the pathways between the genetic variation and perhaps changes at the brain level or changes in cognition or changes in behavior.

>> So you said this particular study you recruited people with an extra Y chromosome?

>> Yeah.

>> All males, you said?

>> That's right. XYY, yeah, as opposed to XY.

>> Okay. And so what typically happens when someone has that extra Y chromosome?

>> Well, it's interesting because--so I should say that we've just finished studying individuals with an extra Y, but they're one subgroup of a broader family of conditions that we study, that we're focusing our first efforts on, called sex chromosome aneuploidies, so there are a number of these. Some of the more commonly seen and studied ones are males carrying an extra X chromosome, so XXY, also called Klinefelter syndrome, or males with an extra Y, as we've just finished studying, so we're working through the whole series. There are some conditions that are commonly seen across many of the aneuploidies. For example, difficulties with attention tend to be more common in sex chromosome aneuploidies than non. Or difficulties in early language development, but then there are some features that seem to be more pronounced with particular subtypes, so they tend to come more prominently when you have an extra Y or an extra X. One of the challenges in doing this work, your question was, you know, what typically, what does one see in males carrying an extra Y? One of the challenging things that we need to work around in this field is called ascertainment bias, and that is that, for some conditions, the individuals that we see in the lab aren't a random sample of all the people out there with an extra Y chromosome. So what we've been seeing in the lab is higher than usual rates of things like attention deficit hyperactivity disorder, tic disorders, difficulties with mood, regulation of mood, and difficulties with social interaction. And what we're trying to do at the moment is figure out which of those might be representative or reflect a pattern that's present in the full population of XYY individuals we're not able to see.

>> Why is it different, what you see in the lab versus the general population?

>> Well, it's interesting. So for some conditions, there aren't any obvious outward signs that you have that condition. So people may come to attention because of behavioral issues. So therefore, if you know you have an extra Y and the reason you found out is because you went to a doctor because of developmental concerns, then if you're only studying people who found out they had an extra Y that way, they'll--lots of them will have developmental issues. And it's thought that up to half of males who carry an extra Y don't actually know they have it. So you might be missing out on the group that are walking around with, perhaps, without too many of those difficulties.

>> And most of the difficulties that arise from that condition is cognitive, not necessarily physical disability?

>> That's right, so that's a good question because that's a nice contrast between XYY – when you add a Y to a normal male carrier type, genotype – and XXY. So an XYY, there aren't really many obvious--people can be a bit taller than usual, but there aren't any sort of obvious physical characteristics. In contrast, in XXY, and--that condition is also accompanied by endocrine problems, and those can be the cause that individuals get this detected, if you like, independent of the behavior.

>> Okay, are you also studying females with these type of aneuploidies?

>> Aneuploidies, yeah. Which just means unusual number of chromosomes. Yes, so we're currently studying, recruiting males with an extra X chromosome, and then next we'll be moving onto females with an extra X.

>> And so how did you come to childhood neuropsychiatry? Is that what you do?

>> Yeah, that's right, child psychiatry. So I kind of always knew that I wanted to work with the brain as my organ of interest, so I went into medicine. And then I went to, when I finished my intern training, I went to my, the local psychiatric research and clinical training institute, sort of young and you know sparkly-eyed. And I'd just come out of medical school and sort of told them I'd been wanting to be a psychiatrist for ages, and they said, "It sounds good, but we like to have people to have a little bit more life experience before they come into psychiatry, so go and do medicine for maybe six months or a year. Get toughened up in the real world of medicine, and then kind of come back." So I went to do ER for six months, and in that ER department, it was unusual because it had a separate pediatric ER. So I really started to work for the first time regularly with children as a clinician, and I was immediately kind of hooked, and I knew at that point that I wanted to understand brain disorders and development in children, and I trained in pediatrics with the idea of doing it through child neurology. But in the UK at the time, I think psychiatry was a discipline that was really perhaps a bit more than pediatrics at that point, trying to use neuroscience to push our understanding of these conditions, these developmental disorders. So I retrained in psychiatry with the express intention of specializing in child psychiatry, and that's what brought me into it. I actually didn't start researching until relatively late in my training, particularly as compared to the US. So often in the US, people who do M.D.'s and Ph.D.'s will do the Ph.D. in the middle of their medical education, for example. Whereas I didn't start the Ph.D. until almost ten years outside medical school.

>> So why did you need to get that Ph.D.? Is that what's required to do psychiatry or--?

>> No, so I mean I completed the clinical training to become a child psychiatrist, but I was really interested in trying to think about biological factors, and I wanted to study the brain as it relates to child psychiatric disorders. So I needed to get some sort of proper training in how to think about data and design studies and do research, so that's what I did at the same time.

>> And so you’re, are you from England?

>> Originally, yeah. My family is from Iran, but born and raised in the UK.

>> Okay. Does anybody over there call it England, or is it everybody call it the UK? [Laughter]

>> Yeah, I don't know. I guess when you're in a fishbowl, you don't know what it's called.

I guess I always called it the UK.

>> So when did you move from Iran, you said? To the UK?

>> Well, I was born in the UK, and I went to Iran when I was nine months old. And I was there until I was five, so my first language was actually Farsi and I grew up there. And then the revolution happened in '79, and like a lot of Iranians, we left. I had been in the UK since then except for three months when I sort of hitchhiked around when I was 24.

>> Oh, yeah, got to squeeze that in there sometime.

>> Yeah, that was a journey of discovery.

>> Do you have any memories of your time in Iran?

>> It's funny, you know, because I have memories, but they've shifted a little bit in that I remember remembering, and when I was remembering say 15 years ago, they were memories where you had an experiential memory, but now it's a memory like you might remember when the World War started, so it's like a fact rather than a personal experience. It's kind of weird. Even though it relates to something I experienced anyhow. So I remember, you know, when chocolate in hot countries can kind of go white, I remember that.

>> Okay, cool!

>> And heat.

>> So what was your life like then when you got back to the UK? Maybe you could talk a little about your childhood? Were you always interested in science or the brain in some fashion, or how did that come about?

>> I think I was. My, my--I don't know if this is true or a story that's been sort of put in me, but I was one--of the things I enjoyed doing was sitting with my granddad in Iran, and he would tell me stories. But the stories he'd tell would be physiology stories, so like how the heart works. And I think, you know, I don't know to what extent it was personal inclination or experiential kind of shaping, but I've always been interested in biology. I've always loved it, so that kind of, and being curious, I guess. So those two things kind of went together.

>> And you might have already touched on this, but how did you find your way over to the US then to do research here?

>> So what happened with the US is you know I was saying when I was doing the science training, when I was training to become a child psychiatrist. The way that happened is it was funded by a body called the MRC, the Medical Research Council, which is a bit like the NIH as a funding body. And they had this scheme then. I don't know if they still do, but in the three years that they'd fund, one of those years you could go away to a center of excellence and learn something and then come back, and that was the first time I came to the States in 2008 to 2009. And I came here to learn how to do developmental neuroimaging. I distinctly remember sitting there in my office by the restroom in my research institute in the UK with the gentle gurgling of the pipes in the background, reading these papers that were coming out of the lab here. And they were just an order of magnitude, the sample size, the image processing methods. It was like waiting for a new album to come out from, you know, your favorite group. You know, so I would pore over these papers, and it was just inspiring. And I remember coming here and actually being able to begin working with the people who were generating that work that had been so inspiring. So it was a great experience that first year. It was really--hooked me.

>> And was that at the NIH?

>> That's right. It was at the Child Psychiatry Branch, so it was with Judy Rapoport and Jay Giedd. So it was a fantastic first taste, and in many ways, I'm kind of still, I still very much feel in that space, sometimes. It's one of the things that's very engaging about the Intramural community is that you know people say some, you know, you're limited just by what you can think of. You know, so well supported and such a special environment for doing big dream science, really. I find that very energizing.

>> When you joined Dr. Rapoport's lab, were you a postdoc at that time? Or so now you're a Lasker, you're a clinical research scholar. Is that what you were at that time? Or--?

>> No, I came as a special volunteer, so I was paid by the UK, and I was a Ph.D. student still. It was the last year of my Ph.D. So then I, in 2009, I went back to the UK, and that was a hell of a year. Went back to the UK, finished off a Ph.D., finished my clinical training, started a family. And then moved back to the US. All in one year.

>> With your family too?

>> Yes, that's right, that's right. My wife who was pregnant at the time, and then a daughter was born here.

>> How many kids do you have now?

>> One so far.

>> And do you run little experiments on her to try to figure out what you want to do in the lab?

>> No, no, she'd suss it out pretty quickly.

>> So then when you finally came, you moved over here with your family. Was that to become a Lasker Scholar?

>> That was into a postdoc position. And then I was a postdoc for a few years, and then became aware of the Lasker scheme, yeah, and I've been on the program I guess since 2015.

>> Cool! And so what, what sorts of tools and technologies do you use regularly in your research?

>> So a big tool for us is neuroimaging, and particularly structural neuroimaging, although we're moving to different forms of neuroimaging. So a lot of our lab is focused on trying to understand patterning of the human brain through these scans, these structural scans that we gather in typically developing participants and individuals with genetic conditions. But we also study behavioral measures that we get from detailed interviews with the families or questionnaires, and increasingly we're starting to study genomic information. So measures of gene expression, either from tissue that we get from the parents or from public databases. So one of the things our laboratory has been working on quite intensely is to generate maps of how the brain is changing or how the brain is different structurally in say a given genetic disorder as compared to typically developing youth. And then we take that difference map, and we align it to large publicly available databases of patterns of gene expression in the human brain, and we use that to try and rank genes that we think might be particularly relevant for the brain changes we're seeing.

>> Interesting. And you had a big paper come out recently that--I believe what your paper said was that, if one brain is larger than another, there's different parts of that brain that are relatively increased more? So what are the differences in those different parts of the brain? Why do some parts of them get bigger in larger brains than other parts, and do those different regions of the brains have different purposes or functions?

>> That's a great question which we're still sort of working on. Maybe before I answer that specifically, just to sort of give you the context of why we did the study because we've been talking a lot about our interest in understanding neurodevelopmental disorders. So actually this question is, this paper was focused just on typically developing individuals. I didn't actually include any patients. But--and we were interested in this question about how the shape of the brain varies as a function of its size. And that's what led to this finding that you mentioned. Some parts are unusually sort of disproportionately expanded in larger brains whereas others aren't. But the thing that got us to asking this question was actually from the patients. Because when you--for many neurogenetic disorders, the total size of the brain is altered. That's a very kind of strong finding, particularly in the sex chromosome aneuploidies. When you add an X chromosome, the whole brain tends to get smaller. And when you add Y's, the whole brain tends to get larger. So you have to deal with brain size, so if you want to ask the question which bits of the brain in this patient group are unusually small or large, relative to controls, you've got to deal with the fact that the whole brain can be altered in size. So you have to control for brain size, and so what that means is you have to understand in order to pinpoint anatomical changes in patients spatially, you've got to first understand the question are there patterns in how the size of subcomponents of the brain relate to the size of the whole brain? And that same thing comes up with sex differences. So in child psychiatry, differences--males and females differ quite consistently in their risk for mental health issues over development, so these new developmental disorders we spoke about are particularly more common in males than females.

>> That's autism spectrum disorders?

>> That's right, or ADHD, for example.

>> Okay.

>> So we do a lot of work also trying to map regional sex differences in brain anatomy, and to do that, we have to deal with the fact that male brains are an average ten percent larger than female brains. So it was this need to understand, a practical need, in a way, to understand this relationship between total size and regional size that led us to really formally try and deal with this issue and generate a map of how local size varies with total size. That question turns out to be quite a kind of deep question independent of the practical things that initially motivated us to ask it. It's been a really--it's a rewarding process, kind of exploring this issue because people have thought about how brain size relates to brain shape most in the context of evolution and development. So you take an--on average, human brains are larger than macaque brains, for example. And if you look at the difference, it's not just in total size, but also in shape. There are certain areas that are disproportionately expanded in humans relative to macaques. So we already knew from evolution that brain size differences between species aren't just linear scaling up of the brain. The brain gets reorganized in its shape, but it had never really been systematically looked at in the context of brain size differences within humans. So basically in primates, there are kind of three ways of getting a bigger brain. You can evolve one, be a human instead of a macaque. You can grow one, be an adult human rather than an infant. Or you can happen to be a, just a larger-brained individuals within your species. So in health, people of the same age, there can be up to a two-fold, almost a two-fold variation in brain size amongst typically developing people. And that's what we were looking at in this paper. We were saying, "If we look as a function of that brain size variation, how does brain shape change?" And then as you say, we found that there's a distributed set of systems that seem to get larger relative to the total increase in the size. And then there are other regions which we call--so the ones that get larger, disproportionately larger, if you like, we call the positive scaling regions. So if the whole brain doubles, they get more than twice bigger. And in contrast, there are other regions, negative scaling regions which get bigger in absolute terms in bigger-brain people, but not as much as you'd expect. They sort of fail to keep up with the total brain size increase. So I think we worked very hard. This study was led by two amazing Ph.D. students in the group, Kirk Reid and then Jacob Seidlitz. And what was really prominent about the way they went around answering this question together with all our collaborators in other institutions is we asked--we wanted to be sure that what we were finding was highly replicable. So we tested it and discovered this pattern in the NIH sample that was actually generated by Judy Rapoport and Jay Giedd, who I mentioned. But we also interestingly sort of verified that the pattern was seen in two other large data sets – all in all about 3,000 human brains. So then when we had established this pattern exists and that it's sort of super robust and replicable, the question was, you know, what is it about? What's it’s biological significance? And the first thing that was striking is the same map of scaling, the contrast between positive scaling and negative scaling just as I mentioned, seemed to recapitulate to sort of echo the map of cortical reorganization I already mentioned at evolution. The same bits that are disproportionately large in humans relative to macaques or adult humans relative to infant humans, are the bits that are disproportionately large in bigger-brained humans relative to smaller-brained humans. So it seemed like there's this kind of rulebook or blueprint that by which there's always this reorganization as you get a bigger primate brain. So we then carried out a series of analyses to try and get just that question you asked probably too long ago, and I've been rambling.

>> That's alright because the background's important. I'm restraining myself to jumping to all these wild like conclusions and questions that probably some people would, would have fun with.

>> Feel free to jump in. Stop me any time. But when, you know, we found this sort of seemingly strongly conserved relationship between brain size and brain shape, and then we started to answer that question that you asked, you know, what is it about these regions? For example, did these hyper expanding regions, are they distinctive in some way? So we conducted a series of analyses. We took the scaling map that we'd just made, and we compared its spatial pattern to other maps that already existed in the literature. So maps of functional networks in the brain. Maps of brain, why the brain's divided up according to its cellular composition, the maps of gene expression in the brain or energy consumption. And two big messages came out from this really, that the red regions, the hyper-expanding regions, seem to be very important for integration, for combining information across other brain networks, and so representing the highly abstract level. And then the second big signal above integration, beyond the integration or alongside it, it was expense. So they weren't only expensive in that it costs money to build more brain, and these things are defined by the fact that they get big, so you have to build them, but they're also a bit greedy, greedier relative to other brain regions at rest. So these hyper-expanding regions tend to soak up a lot of oxygenated blood, and they have gene expression signatures that suggests they have a high expression of genes important for energy generation.

>> And energy generation, not just usage? I don't know if there's a difference there.

>> Yeah, well that's interesting. I guess consumption of the raw materials required, and the sort of molecules needed to convert those raw materials into energy.

>> Got you, okay. Cool! Yeah, I mean it kind of seems like it would make intuitive sense that if they are integrating all these different systems, they would need a lot of energy to do that, right? Or maybe not?

>> Yeah, I mean that was one thought we had. What's interesting is that they get disproportionately large as the brain increases. So it sort of implies that something about having a bigger brain is requiring these things to be preferentially expanded, and we have a number of hypotheses about what that might be, but to be honest, we don't really know because we're measuring millimeters-squared surface area by computer analysis and brain scans. But it'll be great to know what's actually happening in those brain region to make them disproportionately large. Is it they have different numbers of cells? Or the shape of the cells is different? Does that apply to all cells or just some cells? We have some ideas about the answers to these questions, but we're not sure. We're going to try and become more sure by doing a study where we actually analyze the cellular composition and the molecular composition of these brain regions from postmortem samples.

>> A lot of people might guess that a larger brain means you're smarter, especially when you think of humans versus macaques. There's also, I imagine, there's probably a lot of humans of the same age and some sort of same characteristics who one has a smaller brain, one has a larger brain, but they're both pretty much equally, quote-unquote “intelligent” across however you want to measure that. What's the truth? Does a bigger brain mean that you can process more information or take in more information? Or is it like you also said maybe just the cells are bigger, maybe they're just maybe fatter or something?

>> Well, there is a--in terms of the data that's been sort of analyzed to address some of your questions, there is a pretty stable finding that there's a moderate correlation between total brain size variation in humans and IQ variations. So, on average, having a larger brain tends to be associated with having a slightly higher IQ than having a smaller brain, but that relationship is not super strong, and as you say, there are many instances where someone can have a smaller brain than someone else and have the same IQ or higher IQ. So it's not a perfect deterministic relationship, but there is a strong--there's a strongly reproducible trend that those two things are correlated. And we found that in this data set, that we found people that had larger cortical sheets – which is closely related to brain size, it's one facet of brain size – tended to have a higher IQ. And we also showed by definition that people who have larger cortical sheets have this cortical reorganization – you know, the red bits getting--the positive scaling bits getting larger, and the blue less so. But when we control for brain size, inter-individual differences in this scaling map weren't related to IQ. So above and beyond brain size, the extent to which you show this reorganization is not predictive of your IQ. But this reorganization is wrapped up and very much part of the brain size variation which is associated with IQ. So I think my current thinking of it is that a map doesn't really inform, or our data don't seem to suggest that this map is closely related to the observation that larger-brained people tend to have on average a higher IQ. But what it is telling us is about the organizational needs of the brain. Larger brains are having to construct themselves differently in a very consistent way. And that is telling us something about the way a brain is built. So one analogy that we used in this paper is you know, if you take a garden shed and want to make it the size of a mansion, you can't just blow it up linearly, because it will fall down. You have to actually construct it differently, and you probably put more reinforcements in the bits that are going to be more weight-bearing, for example, right? So that's how I think about this brain map in that, by observing how the brain is having to restructure itself as a function of size, we're getting clues about the kind of architecture, if you like, of the brain. And that, presumably, if the brain's nature is spending its money, it's doing it for a reason. It's quite stingy nature, right? A bit tight?

>> Yeah, it seems like integration of all the different areas would make sense to prioritize, at least from my thinking as a non-scientist who doesn't know much about this. It means you can process your environment faster--information from your environment faster maybe?

>> Perhaps. And as you say, if you're, if integration means combining incoming data from the rest of the brain, it may become superlinearly hard to do that as the brain gets big. You double the amount of incoming information, it may be more than double difficult to make sense of all of that information and integrate it. Yeah, those are some of the ideas that we've been thinking through. And just to sort of link back to the, to the clinical work, what's been fascinating is that this set of systems that seems to become disproportionately large in larger brains also seems to be a point of convergent vulnerability across a whole range of neuropsychiatric disorders, so we're finding that if we take children who have neurodevelopmental disorder for, say, ten different reasons – ten different, say, genetic causes – and we ask are there regions that always seem to be altered across these conditions, those regions fall within this system that's hyper-expanded. So it's not just being invested in by biology by being made disproportionately big and being energetic and expensive, but it also seems perhaps to be especially relevant for how the brain is altered in disease, and that's what we're following up now.

>> And so the blue regions – the regions that have negative scaling, so they're smaller – they don't grow as much as the rest of the brain. What are those regions doing? Is there a theme across those?

>> Yeah, so those regions tend to be involved in sort of more basic primary processing of incoming information, so the parts of the brain that process incoming visual information and the parts of the brain that process sensory information will help us plan movements – the sensory motor cortices – those are members of this negative scaling system as well as these limbic regions, as they're called. So sort of underneath and inside the brain.

>> The limbic, is that like the reptile brain?

>> Right, it's been, exactly. It's been referred to as the reptile brain. They're kind of parts of the brain that are more traditionally associated with emotional processing, drive, appetites, value placement on the environment. So there are these kind of consistent functional themes that seem to distinguish the negative scaling, positive scaling regions.

>> Yeah, so one of the crazy questions that--well interpreting science is always a challenge, particularly for non-scientists, and it's great to go after sensational type of headlines and stuff like that. So I'll just ask you a weird question, kind of just to get your take on it. So does any of this point to maybe we're evolving towards higher IQ and lower emotional intelligence in any way? Or we don't need--like our eyes are not getting better. They're probably getting worse, and our sense of smell and a lot of our physical stuff may be getting downgraded just because of our lifestyles, but maybe our brains, since we're plugged into information all the time, we need to--?

>> That's a really interesting question. I mean, our findings wouldn't speak to that, because I guess that's really about sort of trends in brain organization over time within humans.

>> It's a different--.

>> There was actually an interesting, a while ago, there was something called the Flynn effect where if you--people were finding that if you took IQ tests where they're designed to have a mean of 100, and you tested a bunch of people with them, the mean wasn't 100, it was 110. So there was this strange--people seemed to be getting smarter. But just recently there was a paper that came out where actually the sensational headline, as you put it, is that people are getting dumber. That was the kind of--that's not my interpretation of the work, but that's kind of the way it was presented in the media, so actually now when you're applying these tests, the IQ is not, the mean IQ is not 110. It's sort of drifting downwards. And one of the interpretations of that touches on a little bit of what you're saying, which is that it may be that the way we're engaging with our environment and the sort of skills that are being used and the skills that are being taught are slightly different to the sorts of skills that are being assessed in IQ tests. So you know the way we're engaging with our environment is different, but now, I don't think our findings speak to whether the brain itself is shifting.

>> Does your research look at any benefits to a larger brain or a smaller brain based on the scaling or anything?

>> Not on this paper, no. We tested whether above--we replicated this size-IQ relationship, but we also firmly established that above and beyond that into individual variation, and scaling, once you control for total size, is not related to IQ.

>> You have several studies that you've either done or are doing or will be doing. Most of them, you're working with children doing, doing the imaging?

>> So we studied participants age five to twenty five, and that's one of the challenges in the field is these methods for taking images of the brain are super motion-sensitive, and you could imagine asking--.

>> Asking a kid to sit still?

>> Exactly, exactly. We worry and think and work a lot to try to account for those difficulties. And that's really--I think for the field, that's a real open question that we have yet to tackle. So these structural imaging methods have taught us lots about brain development below two. There are loads of studies that have taken these structural scans from children up to about age two and mapped how the different volumes change over time. And then there are lots of studies that are mapped from five up. But between two and five, there's this complete black hole of information. We don't have any information which is just when many of the developmental disorders we're interested in often first manifest, but the problem really has been just what you alluded to, is try getting a three-year-old to lie still in a noisy magnet.

>> That, that's really what's been stopping people from looking at that?

>> Yeah.

>> Wow.

>> Yeah, to be honest, it's, it seems like a relatively low-level challenge, but it really is probably one of the biggest obstacles to our efforts to understand brain development between two and five.

>> Yeah, I mean it makes sense. Every toddler I've ever met won't do anything they ask them to. They would do what they want to do. So what's your approach to--because you, so you've been collecting that data that's missing?

>> No, that's something I want to do. And--but I think we need to. It's going to take some sort of thought and investment at the team level. You need to have funding structures in institutions be sort of cognizant to recognize the need for special solutions for this challenge. So I think that's more of a medium- to longer-term project.

>> And so I think you mentioned that when you were working in the ER, that's when you started working with children and decided you wanted to work with them for a long time. But I don't know if you said why. What was it about it that made you want to study and help children be healthier, understand what's going on with them?

>> That's a good question. At the time, what struck me was really, sounds a bit cheesy, but the innocence, really. You know that they often, some, yeah, I mean, I guess it was sort of seeing children have difficulties evoked something very strong in me, as it does in many people. So at first, it was just that sort of emotional connection, I think. And then the other element that made it very interesting is, you know, working with children really exemplifies very well a kind of multidisciplinary way of thinking about medicine, so the bio-psycho-social model. And children are embedded within families and society, so when you're wanting to do the best you can for the health of a young person, part of you is thinking about optimizing medical treatment in a kind of traditional--let's say, you know, treating an asthma attack, for example, getting the treatment right for the asthma, but then it's also got to do with the setting the child is in, how effectively they're functioning at school, how to support the family, best support the child. So that holistic way of doing that, I think, is very strong in pediatric medicine in general. And then as I got further into my training into psychiatry and neuroscience, it became very clear, and I think it's increasingly clear to people working in the field, that if you want to understand mental health issues across the lifespan, childhood is such a critical phase. If you take adults and you identify individuals in adulthood who have mental health difficulties, for the vast majority of those individuals, if you look back, there are often sort of things happening in childhood. So it's--it's the root, it's the sort of crucible in many ways when so much of us is formed. And that's fascinating from a life history perspective, but it's also incredibly engaging as a biological question, you know, how we are built. So I think I find that, I find that really thrilling.

>> Yeah! I agree. I heard someone describe it as, you know, when you're a child, you're sort of downloading all this information from the people around you. And then you grow up and you sort of express that information.

>> That's right.

>> So you, you currently have two studies going on? Is that correct, in the clinical center that you're recruiting for?

>> Yes, so the--it's recruited through sort of one mechanism, but essentially the way we think about our work is there are these two parallel strands – well, actually they are interwoven –the studies of brain development and health is exemplified, for example, by the scaling paper we were talking about, and studies of children with genetic disorders, and they kind of inform each other.

>> So this was a very big, interesting paper. What are some of your other most recent, interesting papers that come to mind?

>> One paper that really was very interesting to do, and it's going to be useful for us and hopefully for other people, moving forward, is a method that was developed by a Ph.D. student in the group called Jacob Seidlitz, who developed this technique called morphometric similarity mapping or morphometric similarity analysis. And it's a way of taking a scan, one of these structural scans from a single person, and building a model of how related different brain regions are to each other in that person. What was good about that paper is the creation of this new method, but then Jacob also worked very hard to try and break the method. I've never seen anyone work so hard to--which is a great principle in science. You know the results are so alluring, and his first reaction was, "I don't believe it." You know, “I’m gonna try to make it go away.” But it didn't go away, and it's proved to be a very robust, reproducible property of the brain that seems to actually be aligning with regional differences in brain – in cortical micro-architecture, micro-structure, gene expression, cellular organization. So it's almost as if we can use these relatively crude proxy measures that we get from the scan to start to infer something about the microscopic organization of different brain regions. And what was remarkable in this paper is inter-individual differences in the map of this morphometric similarity could predict up to 40% of variation in IQ, and that really, you know, none of us quite believed it when we saw the numbers. But we worked hard to show that that's reproducible. And I think, I don't think--I think that's the highest proportion of variance in IQ that's ever been predicted by a neuroimaging measure, which suggests it could be a useful probe to use in patients. This is the study was all in health, so what we're doing right now is applying this morphometric similarity measure to the patients with genetic disorders. So we're really excited about that! And I guess the other thing I find that we're really excited about right now is it's less technical, but it's perhaps more immediately useful, which is the work that we're doing with patients with aneuploidy, because often we find that they aren't conditions that are particularly well known, and a common experience for many of the families is going to a doctor, and you know, there not really being a great background understanding about that. And that's--from the physician's perspective, that's kind of understandable if it's a relatively unusual condition with relatively little known about it. So we've been doing lots of work that's just trying to really describe in detail what sorts of difficulties young children with these conditions can have, young people with these conditions. And we want to, we're working to publish those findings so that hopefully, there'll be more quality information at easy reach which would be kind of, if it works its way through the system, could actually improve the experience of the families who are affected by sex chromosome aneuploidies. They sort of move through the medical and educational system, and that's something else that we're very passionate about.

>> So I also noticed that you're very active on Twitter which, I don't speak to a lot of scientists who are, and NIH, certain institutes and centers are having, putting effort to get their researchers out there, explaining their work to the world. How did you come to be such a prolific Twitter tweeter?

>> I think I sort of signed up quite casually. I don't know how long ago it was but it has become such an important part of my scientific life. I mean, if I think of the proportion of papers, new papers that I hear about, almost 90% is through Twitter.

>> Wow, just from the people you follow, tweeting it out?

>> Yeah, yeah. I mean it's, it's been a really thrilling kind of experience. And if you, you know, as you say, through the people you follow to have the world curated by amazing people and hopefully contribute to that curation by sharing things that you find interesting that other people in your community might do. It's, that's really powerful, so I think the curation of information has been fascinating. And the other thing that's, you know, remarkable about it is, you know, you can be in, you know, aisle seven of Home Depot and kind of have a question about something, and causally post it. And you know, 20 tweets later, you're in this wild discussion with experts in this field about something that you were just randomly wondering about. And that actually, those sorts of experiences on Twitter have really helped to generate a lot of sort of interesting connections, and but also new questions. So I find it, I'm really floored by how important and impactful it is for sort of organizing and assimilating information, but also sort of sharing ideas and generating new ideas. So I've only recently started having the experience of meeting IRL.

>> Oh, yeah! [Laughter]

>> With Twitter people, finally meet in the flesh.

>> In Real Life.

>> Yeah, yeah, right.

>> How does that come about? So you've met some of your followers or people you follow in real life?

>> Yeah, exactly. And we sort of, you know each other through Twitter, and then you meet in the flesh.

>> By chance or do you plan that through Twitter?

>> Well, it happened, we have planned actually through Twitter in some instances, but even sort of at conferences you post and you realize you, you follow someone and they follow you. Yeah, it's incredibly valuable. I think the community's growing fast. That's my impression. Is that your impression too?

>> Yeah, I think so. I think a lot of people sort of have their preferred places to go for info, and for people who get connected with the right followings and know how to use Twitter well, I think they can really rely on that for--they hear about stuff there first, like you said.

>> Right, I mean it can--there are also, I guess like any human community, it's got its darker sides. I think people can, you know – particularly in the academic subcommunity – for some people I think it can be a way of being a bit more aggressively critical than you might be if you sat across the table from someone, and there's the pile-on culture which I think is problematic, too. But you know, that's about us, not about Twitter.

>> Yeah, [laughter], and so if someone wanted to follow you and follow your research or tweet some cool papers at you, they might wonder what is bogglerapture, which is your Twitter handle.

>> Totally. Bogglerapture is like a naively and perhaps poorly chosen Twitter handle that gives you a sense of how casually I signed up. [Laughter] But in retrospect, [inaudible] but I think, I guess the reason it came to mind is it sort of for me concentrates the intensity of something like Twitter where, you know, that you can boggle at the sheer depth and breadth and diversity of information and that can kind of make you rapturous. So voila, rapture.

>> And so as a Lasker Scholar, did you say you started two years ago in the Lasker Scholar program?

>> It was about three, I think.

>> Three years ago? And so you've got, is it five years total? I have my numbers all wrong on this.

>> Yeah, well it's shifted a little bit over time, but I think that the thing that's remained, that you've been at the program has sort of evolved over time, but I think the element that's remained continuous is the idea is that people would come into the Intramural program through the, through the Lasker scheme and then proceed as a usual sort of tenure track clinician-scientist. And then you, when you get to the point of being assessed for tenure, then at that point, if all goes well, you can then either stay in the Intramural program as a tenured investigator, or have your opportunity to transition out with perhaps some support funding. And the exact timing of that can vary, but I think for most people it's sort of six to eight years.

>> So what would you say is, what's one of the biggest questions that you hope to answer in the future? You've talked about several already that you've been working on, but where do you see your research going in a few years?

>> I think the one that has been on my mind a lot recently and on the mind of people in the group is this issue of selective vulnerability. So if you carry, say, one of these high-impact genetic variants, a simplifying assumption that's reasonably safe to make is that most cells in the brain would have this variant. So in the individuals we study with XYY, it's reasonable to assume there may be some variations, but they're in most cells of the brain. But not all systems are impacted the same way, and we see that through behavior and that there can be domains of attention or emotion regulation that are differently, that are more severely impacted than other domains. But then we also see it structurally in the structural scans. There are particular bits of the brain that seem more obviously altered in their organization than other parts. And that to me is a fascinating and, you know, impactful question. How is it that the brain can develop carrying these variants? There are only some systems that seem to be really bothered. And if we can understand that, if we can understand the basis for this selective vulnerability within the same person's brain, what makes one system within their brain more vulnerable to a genetic variant than another, then that's a, that's, that could lead us to some really powerful insights because if we understand, if we get the answer to that question, we then understand what factors can kind of moderate the impact of a genetic variant on the brain. And that potentially starts to get us close to, in the long term, finding treatments that we might be able to use to mitigate some of the developmental difficulties that can arise. So understanding selective vulnerability I think is a deep one.

>> Well, I wish you luck! That sounds very interesting.

>> Thank you.

>> Is there anything else that you might like to share about what you do at the NIH? Or your life as a scientist in the Intramural program?

>> Yeah, thanks for giving me the opportunity. I think the one thing I'd say, well a couple of things. One thing would be just to emphasize the teamwork, and how many people it takes to do this work. You know, I'm lucky to work with an amazing group of colleagues that span-- particularly if you're a clinician scientist, there are people who now team, that specialize in talking with patients, characterizing the sorts of difficulties they have, giving them advice, all the way through computer engineers who won't have contact with the patients, typically. So really what I think is thrilling but also really important to kind of recognize for funders and policymakers is that it takes a lot of people, and a lot of people with diverse skills, to kind of find a common space where they can kind of work together. That's one thing. The second thing that I'd really like to make sure to acknowledge is the sort of vibrance and power of the student community here, the trainees who really are such a critical part of the endeavor. You know we're really glad and fortunate in my group, the Developmental Neurogenomics Unit – the DNU, as we call it – to have, to have some amazing trainees come through.

>> Are there college students that come and train with you?

>> Well, they come through--there are a range of sort of points that people can come. The earliest one would probably be summer students who might be in high school perhaps, or to the postbac IRTA scheme is a big scheme in the IRP, in the Intramural program. These are people who have done their first degree, and then they'll typically come here for a couple of years, and then from there go onto the next stage of their training. So many people in my group have either gone on to do straight Ph.D.'s or M.D.'s, or M.D./Ph.D.'s after their two years here. And then there's also a smaller program for graduate program partnerships. I mentioned Jacob Seidlitz and Kirk Reid, and they're both on this very interesting scheme, NIH-OxCam scheme, which is about four years, and people earn a Ph.D., which is awarded at either Oxford or Cambridge, but it's part of a shared studentship across the two institutions. And then there is the postdocs and other types of positions for later on in scientific training. But it's a really important part of the community, especially because we aren't an academic institution, so it's not like you've got a campus kind of packed with students. So I think it's really important to try and promote and support the student body, the trainee body here in the IRP. So I guess that's the second thing I'd say.

>> Yeah, it's interesting. We've got so many students here working with Principal Investigators and doctors and nurses and all sorts of people here mixed together. It's a very cool environment.

>> Yeah, yeah it is.

>> What do you, what's most important to you in a mentoring relationship? Or do you have any, I don't know, unique approaches or takes on how you look at mentoring?

>> I think taking it seriously is an important kind of first step, but also recognizing the importance of sort of flexibility and tailoring your style to different students. I think, you know, you mentioned Twitter. Sometimes on Twitter, there are the kind of people who post the ten commandments of--if to be a mentor, you must do these things. And I think, you know, it's interesting when you see the responses from students, some people respond and say, "Absolutely." Some people saying, "No way! If my mentor did this, it would be a nightmare." So I think being attuned and responsive to the students' needs combined with being highly motivated to support them and caring about how they're doing and recognizing the preciousness, really, of the time that we have with trainees, you know, to come when you're 22 to 24, you're interested in the science, and you give two years of your life as a postbac to the IRP. That's some super precious time for them and so the responsibility, I think, is it's important to really have a sense of just what a privilege it is to be able to work with and train people at that critical stage.

>> That's where they figure out really if they want to stick with science as a career or if they want to do something else.

>> Very often, yeah.

>> Cool! And I don't know if I interrupted you. Were there, was there a number three that you wanted to address?

>> No, I think it's probably safest for me to stop with two.

>> Okay, cool.

>> Alright.

>> Well, I really appreciate all your time. Dr. Raznahan. It's been great to meet you and super interesting. And I'll definitely be following all of your research.

>> Thank you so much for your interest in the lab and my work, thank you.

This page was last updated on Friday, February 9, 2024