Podcast: Meet our Researchers

Gil McVean

Statistical Genetics

Prof Gil McVean is the Head of Bioinformatics and Statistical Genetics at the Wellcome Trust Centre for Human Genetics. His research covers several areas in the analysis of genetic variation, combining the development of methods for analysing high throughput sequencing data, theoretical work and empirical analysis.

Statistical Genetics

STATISTICAL METHODOLOGIES

Genomics and Genomic Technology have a powerful influence on understanding disease, and we believe that they have huge potential to take that further into diagnosis and  treatment options. Statistical methodologies and skills are needed to make sense of the incredibly complex data generated from genomic technology.

Translational Medicine

From Bench to Bedside

Ultimately, medical research must translate into improved treatments for patients. At the Nuffield Department of Medicine, our researchers collaborate to develop better health care, improved quality of life, and enhanced preventative measures for all patients. Our findings in the laboratory are translated into changes in clinical practice, from bench to bedside.

Gil McVean: Statistical Genetics

Q: What is statistical genetics?

GMcV: Statistical genetics is the study of genetic variation. Most obviously that is genetic variation in relation to disease - how we look, how we behave and so on. But it is also the study of genetic variation in the context of how it came about and what it can tell us about very fundamental processes. For example I have been studying recombination for maybe ten years now and we are using genetic variation in natural populations to understand that. We also use genetic variation to understand about history, how people have moved around the globe, what kind of selective forces and evolutionary pressures have been shaping populations over that time.

Q: How does studying genetic variation help us to understand complex diseases?

GMcV: Perhaps it is easiest to explain that through an example; we have been working with a group here who are interested in Craniosynostosis which is a nasty cranial malformation that you get in children. Typically these result from new mutations that occur when a father or a mother transmits their genetic material to a child. These are very severe and of course that child is very unlikely to go on to survive or reproduce, unless there is some strong treatment. So that is one way in which the disease occurs. But actually that is by far and away the minority way by which disease happens. Most of the genetic influence on disease comes through inherited mutations so if you get MS, heart disease, stroke or something like that, the genetic factors which shape that are things that you have got from your parents and they got from their ancestors. So these things are common in the population often and they have very subtle effects. What we do in statistical genetics is to look at a whole cohort of people to try and work out which genes are enriched in people that get a particular disease, but very rarely are they definitive - you have this mutation and therefore you are going get this disease. So by studying these genetic variations the sort of things that we hope to be able to do are to identify which genes are involved in disease risk, but perhaps more generally which pathways, which ways and which cells, function and interact within the environment are much more important. So for example with Multiple Sclerosis, which I have been studying recently, we have found that the majority of the genetic variants that lead to an increased risk of MS are associated with the immune system and, in fact, a very particular part of the immune system. And that opens up new possibilities for trying to understand exactly why you get the disease.

Q: What are the most important lines of research that have developed over the past five or ten years?

GMcV: I think that the single most transforming factor in the last five years has been the emergence of whole genome sequencing as a technology that we can use routinely in the lab to try and understand why people get a particular disease. For example, in Oxford we have been sequencing 500 individuals with a whole variety of different clinical disorders to try to understand which genetic variants they carry are the ones that increase the risk of the disease. In some cases we have very strong mutations but in others these re much weaker effects. It has been a very transforming technology but what we have had to do as a community to work out how to use it has been to assemble large international consortia to push the development of both methodologies, but also the collection of large cohorts that we can study complex diseases. And one of the things I have been doing is helping to run a project called the Thousand Genomes Project, which is actually sequencing around 2500 people for the purpose of trying to understand what genetic variation looks like in the human population, so that when we go to a disease population or cohort we can sort of work out what they have got that the normal population does not.

Q: Why does your line of research matter, why should we put money into it?

GMcV: Most people are fairly aware that genomics is a set of technologies that can have a very powerful influence on understanding disease. For example, in cancer particular mutations that you get in those cancers determine which treatments are likely to be successful or not. You might have genetic variation that influences how you are going to respond to a particular drug - whether you have a bad reaction or a good reaction. That is where genomics is at the moment as a set of technologies, but we think that there is a huge potential for it to go much further so that if you come into the clinic and you have got Multiple Sclerosis we might be able to say a lot more on the basis of the genetic variants that you carry about your treatment options. So we think that genomics and genomic technologies are very powerful in science, but to make sense of the data that comes out of them you need very strong statistical methodologies and skills. The data is huge; it is very noisy and incredibly complex. Teasing out signal from that noise is an incredibly difficult problem and that is where we need statistics in it.

Q: How does your research fit into translational medicine within the department?

GMcV: I think the strongest case that you can make for that is the role of genomic technologies and whole genome sequencing in trying to understand particular disorders. Genome sequencing is already used in things like understanding how cancers work, and we think it can go much further and so the Bioinformatics and Statistical Genetics, the group that I head, is working with the Biomedical Research Centre and other clinicians across Oxford to see what sequencing and genome technologies more generally can bring to the clinic. We have had a few successes in that already; earlier I mentioned Craniosynostosis. We have actually found mutations now in several children where they were previously undiagnosed, and that is actually a really important part of that treatment process - identifying the cause of mutations. So I think it is very exciting that we are actually already using sequencing in the clinical setting and we hope that it can go much further.