Professor Marissa Ehringer, the President of IBANGS, discusses some of the challenges and opportunities in the field of behavioural and neural genetics today.
Established in 1996 to promote and facilitate the growth of research in the field of neural genetics, the International Behavioural and Neural Genetics Society (IBANGS) has a global membership who study the genetic basis of a wide range of behaviours and brain disorders together with the underlying neuronal mechanisms using diverse species.
The ultimate goal for IBANGS is to elucidate the molecular pathways through which genes together with the environment affect behaviour.
In an interview with SciTech Europa, Professor Marissa Ehringer, the President of IBANGS, outlined some of the challenges and opportunities in the field of behavioural and neural genetics today, including a discussion of technological advances, the issue of multidisciplinary working, and the role of IBANGS in supporting the scientific community.
Could you begin by outlining how you feel the field of neural behavioural genetics has evolved in recent years? What do you feel are the biggest challenges in the area?
One of the biggest ways in which the neural genetics field has evolved is in relation to the technologies that have advanced alongside it. Perhaps one of the most obvious examples here is high throughput sequencing and, moving forwards, whole genome sequencing and gathering the data from that holds a lot of promise.
In the context of human genetics and its relation to behaviour, a lot of work now involves the use of very large data sets, such as those provided by the UK Biobank, while in parallel, in the world of neuroscience, there has been an explosion of technology that can be applied to behaviour; CRISPR/Cas technology being an obvious example.
The ability of neuroscientists to be able to really target specific genes as well as specific neuronal regions in the brain, at specific time points, sometimes even in certain cell types, has also served to significantly advance the field at a more basic science level.
Ultimately, the challenge is going to be in putting these two things together and then translating that into understanding mechanisms at the neuronal level so as to see whether or not some of the things we are able to do in the brains of rodents are things that we may be able to do in the brains of humans.
We have learned that it is hard to do effective treatment at the whole organism level because of the many off-target effects, however, so this will certainly be a challenge to achieve.
Is enough being done to ensure that the big data sets made available by, for instance, the UK Biobank, are accessible and, indeed, usable via standardisation?
Accessibility has become a lot easier in the last five years or so. For UK Biobank, it is relatively easy to apply, and while it takes time and quite a lot of paperwork, if you have the right training and skill set, you can gain access.
A balance needs to be struck, however, in order to ensure that these data are being accessed by those who are able to use it in the right way. For example, in the past in the field of genetics there was a period when some people were generating data themselves or accessing data from elsewhere (public data, for instance), and they used this to add a genetic element to their study. But, sometimes, these people were not geneticists, and much of the work that was produced couldn’t be replicated.
Are there inequalities when it comes to the availability of data or perhaps in the amount of science being done in some regions?
The Psychiatric Genetics Consortium was established some 10 years ago, and at the beginning this primarily only included investigators who contributed data; but that has changed in recent years. And, of course, there are some inequalities in some less developed countries where there just isn’t as much support and funding for science in general.
In the USA, the National Institutes of Health (NIH) has certainly done what they can to encourage data sharing. If someone receives funding from the NIH for, say, a genome-wide association (GWAS) study that is going to collect whole genome data, then they have to make those data available to other investigators; they have to put them in the database of Genotypes and Phenotypes (dbGaP), and that has been true for many years.
There are, however, some logistical issues with being able to harmonise the data that you might obtain from dbGaP, and it can also take a significant amount of time to access those data. For example, I know people who are conducting this type of research who have decided to move away from dbGaP in favour of the data offered by the UK Biobank, because the latter offers a large amount of data which does not require as much harmonisation or standardisation.
As such, this conversation has led me to believe that there would be great value in an effort designed to simply combine all the data from the dbGaP into a single large dataset; that would become a great resource.
Do you feel that a more interdisciplinary approach is required to better address the challenges inherent in studying the genetic basis of a wide range of behaviours and brain disorders?
At the Institute for Behavioral Genetics (IBG) at the University of Colorado, that has been our belief for the past 50 years. As a new assistant professor I began looking at nicotine receptor genes in human populations because IBG had a senior investigator who had studied those genes in mouse models for some 30 years. It was found from GWAS studies that those genes were indeed involved in smoking behaviours, and subsequently we have been able to quickly move those findings from humans to study them in mouse models in order to gain a better understanding of molecular function.
This particular concept is important to me because I conduct both human studies and molecular studies, and mouse studies, and I believe that combination is needed in order to actually advance the field; but it is difficult. It is hard because there are different scientific and technical languages used by those coming from the different areas – those working on human genetics use a different language to those working with animals, for instance. And, it can take a lot of time and concerted effort to bring people together who do speak different languages and to get them to try to understand each other.
But that is happening, and it is necessary for it to happen even more moving forwards; it doesn’t advance the field towards improved treatment if work on the genes that are discovered from GWAS studies in order to better understand them doesn’t take place. In order for that to happen, the statistical geneticist has to interact with the neuroscientist, but that is a challenge because they are very different cultures in some ways, and there are barriers that have to be broken down in order to make that happen.
Genome-wide association studies and next generation sequencing studies have begun to shed light on some neurodegenerative disorders. Where do you feel future work should focus here?
There are a couple of directions being taken now by those working in this area. This can involve moving towards looking at gene-by-gene interactions or network analyses, for example, or even potentially gene by environment interactions.
Gene by environment studies were seen in a negative light for quite some time because people were doing them without sufficient power and very little was replicable. But the sample sizes are now getting big enough that it might be feasible to start doing some gene by environment interactions in intelligent ways, and people are working towards that at the level of human genetic studies.
It is going to be important for us to take the variants that are identified in humans and to try to study those in animal models so as to understand their function, and this brings into play the role of pharmacogenetics – if you have a particular variant that know is associated with a behaviour and have both versions in the mouse, then you can look to see whether there are different responses to drugs and so on.
The challenge there is still going to be the fact that a single variant is probably not going to have a really big effect, and so we will need to develop new ways that allow us to look at combinations of variants in an animal model to see how these different combinations work together for an overall larger effect size.
Do you think that there is an adequate amount of progress being made towards precision medicine in this area?
People are trying; and there are efforts working towards clinical studies in humans too.
My own area of expertise is nicotine and alcohol addiction, and the variant that has been most widely associated with smoking behaviours has been the subject of pharmacogenetics studies, where different alleles have been identified in different people’s brains and which could be used to identify which treatment could be a success. The results from these studies have been somewhat mixed. Some early data suggested that this variant might really be predictive of whether or not a person would respond to different kinds of treatment, but later results were not as clear.
Additionally, and this is not necessarily directly related to genetics, in the context of many psychiatric disorders, especially addiction, there can be a perception that people can undergo treatment for six months or a year and can then be considered ‘well’ again. Of course, this is not the case.
The parallel has been made with patients who have diabetes or heart disease: these people cannot be treated for a short period of time and then left to fend for themselves; and the same is true for those who suffer from addiction. While many people may understand this when it comes to common psychiatric disorders such as schizophrenia or bipolar or autism, the same recognition that depression or drug addiction is also a disease that isn’t simply going to go away hasn’t pervaded the conscious thinking of most people. As such, this is certainly an important component of being able to translate what we find into effective treatments.
What are the biggest barriers to translating research in this area to clinical applications? Are there issues with funding?
There are indeed issues with funding, and part of that is because the size of the effect sizes of the many genes that are associated with behaviours are quite small, which means very large, and therefore expensive, clinical studies are required if you want to be able to translate that into some kind of clinical application. This also requires a co-ordinated effort across different teams of investigators, all of whom might have different ideas about how the study should be conducted, to move that forward, which complicates things further.
An additional barrier in behavioural genetics is the fact that the organ that you want to treat is the brain, and the brain is harder target than many of the other organs in the human body. What is more, we simply don’t understand the brain that well yet, and so it is harder to focus treatment.
Of course, some research is taking place to develop tools to do that, and, as we have discussed, there are already some good tools that are available to enable that work to be done in rodents – we can take microRNAs, for instance, and we can target specific regions in the rodent brain. However, the things we can do in the rodent brain are not things that anyone would ever consider being able to do to a human brain, and rightly so. These challenges make it harder to be able to translate some of what we might view as successful treatments in the animal to a treatment in the human.
What role does IBANGS play and how do you predict this will change moving forwards? Given the changing landscape we have discussed, will IBANGS similarly have to evolve?
This is a really good question and it is something that the leadership of IBANGS has struggled with for many years. IBANGS is a relatively small society, and that in itself can raise a lot of challenges, not least the amount of work that is required of each of the people involved.
IBANGS is also a unique society in the sense that it includes investigators who are working in human genetics alongside those working on mouse genetics and model organisms that aren’t mammals – there are a number of investigators within IBANGS who, for instance, use the worm or the fly, and a lot of other genetic models of behaviour, and those models can be studied much more quickly compared to the rodent or humans. That multidisciplinarity in the field of neurogenetics is really quite unique.
IBANGS also has a long history of bringing young investigators into the field, and we have received a grant from the NIH/NIAAA that helps to support our annual meeting, providing travel support for graduate students, postdoctoral fellows and young assistant professors.
The advantage of our meeting being relatively small is that it enables those trainees to gain access to senor investigators who are also in attendance, which they might not get at some of the bigger events. This, in turn, helps to build and maintain their excitement, enthusiasm and passion for continuing in science.
The IBANGS journal, Genes, Brain and Behaviour – is very well respected and of which we are very proud – is another significant contribution to the field because people see the quality of the papers being published, and this also helps to disseminate information across disciplines in quite a unique way.
IBANGS therefore certainly serves an interdisciplinary training ground for students and senior investigators alike; we all learn things at the meeting regardless of our level of expertise.
Professor Marissa Ehringer President
International Behavioural and Neural Genetics Society (IBANGS)
Institute for Behavioral Genetics
University of Colorado
This article will appear in SciTech Europa Quarterly issue 27, which will be published in June, 2018.