Correlation is not causation

At the moment, I'm particularly looking at identifying regions in the genome that might be associated with modifying the risk of Inflammatory Bowel Disease (IBD). IBD is a complex, immune mediated disease, caused by a combination of both genetic and environmental factors.

We have a very large international cohort of patients with IBD, including the two major subtypes - Crohn's disease and ulcerative colitis. We also have a group of individuals without a particular disease.

We are looking at whether specific changes in the genome appear more or less in the different groups. This GWAS (genome-wide association study) is going to give us clues of where in the genome we need to look in a little bit more detail.

Taking that forward, we want to understand why those regions in the genome modify risk. What is the mechanism behind it? I'm super excited about the work I'm doing.

We are trying to understand how a specific genetic change might modify either the activity of a gene, or the protein that the gene produces.

We are looking for a molecular explanation of how the genetic changes are having an effect.
We are also trying to understand which cell types are involved. Where are the genes active? We want to put this entire story together.

We use large international databases, where genetic variation has been linked to gene activity, to help us locate the effector genes and cell types. But also within our team here, we have researchers in the laboratory generating data. These include genotyping array data, and single-cell data, from gut biopsies and blood samples from hundreds of people with and without IBD. These types of data allow us to see directly how genetic variation affects gene activity levels in the different cell types.

It’s at a really exciting stage – we know the genomic regions involved, and now we need to interpret them.

One of the things I love most about working on IBD is that we have found many genes involved in the different forms of the disease¹. Already some of these genes are targeted by approved drugs for IBD, with more in clinical trials. So if we can find additional genes, we can find additional potential therapeutic targets. The ultimate aim is to find a new drug target.

As a computational biologist, I think that 10 or 20 years ago, we believed that by now, this kind of problem would have been solved. But Genome-Wide Association Studies (GWAS) – looking for genetic variations that may modify the risk of disease – have turned out to be more complex than we thought.

There is the interplay between common and rare genetic variation, which is now something that I'm very keen on understanding. We’re working with other groups in the Sanger Institute to understand this. It's very interesting to see the intersection of both; they are not isolated.

Well, this is very high level, but it’s discovering new things. That is just ongoing. The thing I like here at the Sanger Institute, in particular, is that we have both a computational team and a laboratory team together. I love that kind of working environment, where we have many interdisciplinary people. I can input into experimental design, because that in turn feeds through into the types of data we will get at the end. I can appreciate how the data are produced, which is vital for analysis. I love working with this great team of people!

There has been very interesting work from the Broad Institute in the US (with whom we collaborate), where they have found a genetic variant that is involved in developing cystic fibrosis might be also associated with a lower risk of IBD².

That was surprising – it will be interesting to understand the mechanism and how these two different diseases might be related, as the symptoms and the tissues involved are so different.

I’ve had many role models. My PhD supervisor, Dr Ana Vega, and postdoc supervisor, Professor Alison Dunning, were both important mentors to me. I’ve also been inspired by women in science, like Margarita Salas. She was a molecular biologist who identified methods of DNA replication, and this still has consequences today – it has made single-cell sequencing technologies much more accurate, for example. But it’s not just for her discoveries, she was a role model for other people. She inspired a new generation of scientists in Spain. So she's fantastic.

I do feel that women in science face many, many challenges. I think there's a ceiling issue - we start off being similar numbers of males and females in the early stages of our careers, but then somehow we don't make it to the end part in equal numbers. There are some great initiatives, but it feels like it’s a structural problem in society, it’s a bigger issue, and we’ve got more work to do on that.

No particular moment in time, but I would like to meet some of the salient women in the past who worked in science. With those people, I’d like to understand how, with all the challenges they had at the time, they managed to have such amazing successful careers.

‘Correlation is not causation’ - that's an important one!