FLG: Could you introduce yourself and tell us about the work you are currently doing at UKRI – UK Research and Innovation?
I’m Rona Strawbridge and would probably describe myself as a statistical geneticist. Since I finished my PhD, I’ve been using genetics to try to understand the regulation of cardio-metabolic disorders (including obesity, diabetes and atherosclerosis) as well as casual relationships between metabolic and cardiovascular traits. I’ve been lucky to work with many fantastic people within international genetic consortia and have learnt a huge amount from those collaborations. Indeed, the collaborative nature of genetics is something I really enjoy. For the last 2 years, thanks to funding from UKRI/HDR-UK, I’ve been using genetics to try to explain why individuals with serious mental illness (such as schizophrenia, bipolar disorder and major depressive disorder) have an excess of cardiometabolic disease compared to the general population.
In cardiovascular and metabolic research, studying intermediate traits (such as lipid levels) in the general population, as well as comparing cases and controls (such as heart attack), has proven hugely informative of biological mechanisms. We are now applying this approach to serious mental illness research. So instead of focusing just on psychiatric diagnosis, we are now exploring traits which are evident in the general population as well as in those with mental illness, such as anhedonia, mood instability, suicidal and risk-taking behaviours.
FLG: What motivated you to pursue a career in this field?
Generally speaking, my interest in this field is because in recent years, cardiovascular prevention initiatives have been very successful in the general population, but the same benefits have not been observed for individuals with serious mental illness. Traditionally, this excess risk of cardio-metabolic disease has been explained by effects of medication, deprivation, substance abuse, sedentary behaviour and poor diet, but distinguishing which factors are causes and which are effects has proven difficult. Genetic variation is stable over time, so combined with recent advances statistical methods means that we can now explore causal relationships. Studies are ongoing to either conclusively refute or identify common mechanisms linking serious mental illness with poor cardio-metabolic health. This is an important question, because if common mechanisms exist between mental and physical illness, then medication currently used to treat cardiometabolic disease could be repurposed to reduce symptoms and disease burden in those with serious mental illness. Similarly, if no common mechanisms exist, there are implications for social and health policy in early prevention of serious mental illness.
FLG: How do you think genetic testing/data being used across the pharmaceutical industry today?
To my knowledge the pharmaceutical industry is using genetic data (specifically results of genetic studies) to prioritise drug development. Where identified genetic variants associated with a trait of interest highlight a mechanism, drugs targeting that mechanism can be prioritised. Depending upon the data available, drugs might be designed to mimic a particular genetic variation. Similarly, if a drug shows potential in pre-clinical studies, off-target effects of genetic variants in the pathway targeted by the drug can be explored. I guess the pharmaceutical companies would be interested in genetic testing only if drugs demonstrate off-target effects only with a certain profile of genetic variations. This might not catch all potential issues, but it could be valuable information to save time and money. Of course, there is a decision about which off-target effects are acceptable, on balance with the condition the drug is targeting.
I guess considering not only the human data, but evolutionary conservation of variants and mechanisms could be informative (under the assumption that more conservation = more important for survival = more serious consequences when there is disruption = harder to cause a meaningful disruption).
FLG: In your opinion, can we reduce the rate of trial failure and the high costs incurred before they become an inhibiting factor in starting new trials?
By doing the stuff suggested above, this should reduce drugs which fail in clinical studies and reduce the serious adverse side effects of some drugs. Given the increasing quantity, quality and openness in sharing of large genetic analyses, this is likely to become more and more robust and informative. An important factor also to consider (which I’m sure the pharmaceutical companies are aware of) is that to date, the majority of genetic data is comparable with a generalised European ancestry population, and therefore does not give the full picture for the global population.
FLG: What do you think is the most exciting thing happening in genomics right now?
The increased awareness, funding and efforts towards genotyping and genetic analysis in non-European ancestry samples, as well as development of methodologies to enable analysis of multi-ethnic samples. Much of what we know from genetics is based on European ancestry samples, which reflects only a small part of the global population. Having a more detailed understanding of genetic variation and its impact on disease on a global scale can only be a good thing. Obviously, there are still challenges, for example disease definitions and measurement and accounting for cultural and geographical differences (to name only a few), but there is growing enthusiasm for addressing these, so I am optimistic progress will be made. These advances will also have significant implications for drug development, in terms of drug safety, efficacy and personalised medicine.
FLG: What breakthroughs do you see happening in 12 months or 5 years?
Hopefully outputs from the efforts as said above will provide valuable information. In fact, understanding of suicidal biology may well benefit, as large worldwide collaborations are required to gather sufficient data to robustly analyse such rare events.