GENES, ENVIRONMENT, THE DEVELOPING BRAIN, AND EVERYTHING IN BETWEEN
By Tzipi Horowitz-Kraus
One of the most interesting questions when researching the developing brain is the level of impact of defined genetic and environmental factors. Dr Armin Raznahan, a Neuroscientist and a child psychiatrist, who serves as Chief of the Developmental Neurogenomics Unit in the National Institute of Mental Health (NIMH), examines patterns of brain development in health and in groups with known neurogenetic disorders. His unique blending of basic and clinical neuroscience may help to identify risk pathways towards common psychiatric presentations, in addition to the insights it provides regarding the specific rare developmental disorder subtypes his clinical research protocols are focused on. I had the honor of interviewing Dr Raznahan, a keynote speaker in the upcoming OHBM 2019 conference, to find out more about his work.
Tzipi Horowitz-Kraus (THK): What is developmental neurogenomics, and what motivated you to go into this area of research?
Armin Raznahan (AR): I see Developmental Neurogenomics as a discipline that is concerned with brain development, and emphasises the role of genetic factors in patterning brain structure and function over development. Usage of the term Developmental Neurogenomics has increased in recent years, and for us, there is an additional emphasis within what I’ve just described on thinking about how genetic influences on the developing brain can contribute to psychiatric disorders. Coming from the perspective of my initial training as a child psychiatrist, there is that clinical element to what I do as well as the basic science questions about spatiotemporal patterning of the brain over development, and how genetic variation can contribute to that.
What got me into it? It’s really a mixture of factors. First, I had a longstanding personal interest in the brain, and good fortune in interacting with excellent inspirational mentors along the way. But also, my training occurred at a particularly interesting time in the science of neuroimaging. It was just when we saw a massive expansion of genetics and the emergence of massive neuroimaging databases. These developments made it easier to look at brain patterns in health and in genetically-defined subgroups. Clinically, I worked in pediatrics before moving to psychiatry, and in the early stages of my career I worked as a clinician in a school for children with special needs, including those with autism.That was the experience that got me hooked on neurodevelopmental disorders. My initial studies compared children with autism to typically-developing controls. In the last few years, though, my work has moved away from study designs that start with psychiatric diagnoses, into studies that take a “genetics-first” approach and start with groups defined by the fact that they carry a known genetic mutation that puts individuals at significantly elevated risk for neuropsychiatric disorders. We then try to understand this risk in biological terms, from a known starting point.
THK: If you weren't talking to brain mappers or scientists, how would you describe your most proud scientific accomplishment?
AR: Well, I’m always wary of pride (smiles). In terms though of the studies that have given me, and those in my group who have done the work, the greatest jolt of excitement ... well I can think of a couple of findings: one that relates to brain organization in health, and another one relating to altered brain organization in clinical populations.
In the first, basic science side of things, one of the most exciting studies for us examined whether the shape of the human brain differs between those with larger or smaller brains. We found that there is this set of cortical regions which become disproportionately large - most prominently expanded - in larger vs. smaller brains, and that these regions are notable for being key hubs of information integration within the brain. It was notable that other studies had shown that these same regions also showed disproportionate expansion as part of brain size increases over primate evolution and development. So, it was a very exciting finding for us, because it strengthened the case that there is this blueprint within the primate brain where there are these requirements to have a reconfiguration of the brain as brain size becomes larger. So, these analyses of brain size effects are a bit like trying to infer engineering principles from looking at bridges of different sizes and noting patterned differences in their construction. Whereas we might know the laws of physics that shape the patterns in bridge building, this approach can provide a window on less well understood design principles in the nervous system. This basic science work also helped us better localize regional anatomical alterations in patient groups that show differences in total brain size from controls.
On the clinical side, I’m excited by a study where we tried to understand selective vulnerability of the brain using publicly available gene expression maps of the human brain. So, when we look at our structural neuroimaging data in patients carrying an abnormal dosage of known gene sets, we see that some cortical regions seem to “care” about the gene dosage change and show altered anatomy, whereas other regions seem less altered. So we wanted to try and understand this “selective vulnerability” that can vary across different gene dosage disorders. We used computational approaches to identify sets of brain-expressed genes that might make some regions more vulnerable to genetic disorders than others. We’re very excited about this work, which is under review right now.
Finally, I should say that none of the work we do would be possible without the amazing trainees in my group. So, as much as there is excitement and pride in the work, there is excitement and pride in the people doing the work.
THK: A lot of your work examines how genetics cause sex-related differences in brain structure. The idea that there are no innate differences between the sexes has received a lot of recent press attention. Your work clearly challenges this. Where do you think the reality of this situation lies?
AR: So, this is obviously a very heated topic, and I think that a lot of the debate and strong emotion stems from a couple of places. One is around the idea of difference, so I think it’s important to stress that there can be a highly reproducible and statistically significant difference between the means of a trait between males and females, whilst there being a great deal of overlap, too. So, to claim that there is a difference doesn’t require there to be a complete separation. If you think about height, there is no doubt that the average height in males is significantly greater than that in females, but there are some women who are taller than some men, and some men who are shorter than some women. So, I think that’s an important thing to clarify at the outset of discussion around this topic.
The other thing is that sometimes people can “jump” from hearing that term “two groups are different” to thinking that the assertion is that “the two groups are not equal”. My approach to this is very much based on the data; I think it’s important in this kind of work not to jump too quickly from observing statistical differences in means to inferring functional consequences. Keeping statistical fact apart from value-laden judgement is very important when discussing sex differences.
I think the third complexity is around the notion of “innateness”. This hinges on seeking to distinguish between sex differences that are relatively “hard-wired” and established in early development in ways that are less dependent on the environment, from those sex-differences that are more reflective of environmental and societal factors. So, saying that you see a difference is distinct from saying what you think that difference is caused by. We have to be aware of the potency and complexity of societal influences as well as biological influences.
Having said all of that, it is clear to me and to many others working in this field that there are very likely to be innate differences between the sexes with regards to brain structure and function. If we look at medicine, we see highly reproducible, stable sex differences in risk for brain disorders. For instance, developmental disorders like autism, ADHD, early-onset tic disorders, specific language disability - it’s very clear that there is a robustly greater risk in males relative to females, and that risk tends to emerge in a particular age-window during the preschool years. At the same time, it’s also very clear that around the adolescent transition, there are other disorders that tend to show a clear female-bias in risk - mood disorders and eating disorders would be two examples. Now, one can’t tell for sure that these differences aren’t environmentally-driven, because we can’t easily run experiments in humans. However, the fact that these differences are tied very closely to developmental patterns, emerge consistently in different cultures, and are reproducibly demonstrated across time, strengthens the likelihood that, in part at least, these differences in disease risk are reflective of some innate differences in brain organization between males and females.
If we now move away from disease risk and think about sex-differences in brain anatomy, as referred to in your question, I think that there is no arguing against the fact that, increasingly now, in large samples, we see these highly reproducible sex differences in regional brain anatomy. These are differences in means, with lots of overlap, and we don’t know the functional consequences of these anatomical differences, but they are highly stereotyped and, I think, it just a statistical fact.
THK: Your recent work also discusses how the environmental influences of socioeconomic status (SES) impacts on brain development. Could understanding this relationship help reduce mental health problems and academic underachievement in those with low SES?
AR: Recognizing that genes and environment can be highly correlated is important. Although one’s work might focus on one or the other, it’s critical to not lose sight of the fact that we all reflect a complex interplay between these factors over time in a nonlinear fashion. The fact that the genome is easier to measure than the environment has led many to focus on genetic factors, but it’s obviously key to not lose sight of the environment within which genetic effects interact and unfold.
The study of ours on SES that you refer to was really a very first step for us into this area. Our work to date has really centered on understanding influences of age, sex and defined genetic factors on brain organization, but we were prompted to study SES because we observed that the SES distribution could often differ between the clinical groups and the control groups we were comparing in our research. So, one of the motivations was to look at whether this factor that differed in group comparisons was associated with inter-individual variation in brain anatomy and we sought to first assess this amongst typically-developing groups. In the paper, we really worked hard to emphasize a couple of things. First, that SES is a complex multi-dimensional construct, which we were measuring in a relatively crude way. And second, that we were absolutely not suggesting that the observed correlation between SES and brain anatomy necessarily meant that the environment was causing or entirely responsible for the observed variations in brain anatomy. For example, it could plausibly be that a set of genetic variations, which influence brain anatomy are correlated with SES. So, I think the importance of being suitably cautious and humble about making mechanistic conclusions from observed correlations cannot be overstated.
THK: What do you think are the most pressing issues in neurogenomics?
AR: Well (laughs), rather unfortunately, I’d say complexity of the brain and complexity of the genome! It’s a particularly challenging field given that you’re taking two massively complex, non-linear, multivariate things that live in time, and trying to understand the relationship between them.
But, I’d say, from the perspective of basic science questions, that some of the things that are at the center of people’s minds right now are trying to understand how genetic effects contribute to and manifest within the cellular heterogeneity of the brain. So, how genes pattern cellular diversity over space and time and how genes operate in cell-type specific ways. This is a huge area that has really only just been opened up to us now by advances in single cell sequencing. One of the other challenging factors in humans is time: the fact that we have this unusually protracted developmental window and the difficulty in modelling that within systems you can manipulate. And maybe a third challenge is understanding how the “rubber hits the road” when we think about environmental influences in development. That’s going to rely in part on improving how we measure the environment, which is a vast conceptual and logistical challenge. I’d also say that another challenge is the capacity of the brain and biology to “righten itself”. We are observing systems that don’t just passively “take hits”, but have presumably been designed over evolution to have some robustness to genetic or environmental insults. So, in some ways, the signals that we see in patients might partly be differences in compensation rather than “pure” signals of the primary causal risk factors.
From the clinical side, I think that one of the profound challenges for psychiatric neurogenomics is around nosology. We still need diagnoses for communication amongst clinicians and patients, and to assist making binary decisions around treatment. So I certainly don’t think we’re ready to “do away” with diagnoses,but at the same time, it is absolutely clear that these diagnostic constructs don’t map onto biology very clearly. So we are left with the question: “Well, are there dimensions of behavior for us to discover that will perform better than diagnoses in terms of how cleanly they map onto the brain, onto genetic variation”. It’s really about the challenge of optimizing how we capture the phenotypic space of behavior and cognition as part of an effort to understand mechanisms for psychiatric disease. That should be enough to keep everyone busy for a few years (or a few thousand generations) !
THK: Finally, what other insights can you give us into your keynote talk?
AR: My talk will focus on the developing brain from the perspective of healthy development vs disease, with an emphasis on an integrative view at multiple levels. So, what can be gained from closely integrating studies of health and disease. And a second theme of integration would be around combining brain data from different scales - for example from structural imaging data and postmortem gene expression data. This links into the third theme I wanted to try and highlight, which is how one might use these integrative approaches to “squeeze” more information out of something like a structural MRI of the brain. I’m continually amazed how much anatomy, as measurable from something like an in vivo brain scan, can inform us. I just think there is so much that can be learned from anatomy, and I hope I can communicate some of that excitement and enthusiasm in the talk. That’s the idea at least! (smiles).