Research Interview Dr Stephen Burgess

Do vitamin D supplements benefit all people equally? What is the impact of body fat on an individual’s risk of developing digestive cancer? How does mask-wearing affect viral exposure?

Homerton Fellow Dr Stephen Burgess has addressed all of these issues over the past 18 months. But he’s not a doctor or a biologist. Instead, he’s a mathematician.

In a career straddling the Medical Research Council’s Biostatistics Unit and the Cardiovascular Epidemiology Unit (both at the University of Cambridge), Stephen uses statistical data on genetics and medical biomarkers to investigate patterns in diseases.

“The fundamental question is why do some people get sick and others don’t. If we just looked at genetics in isolation that would be quite fatalistic; instead we look at what they tell us about modifiable risk factors.”

Stephen can still remember the element of his undergraduate Maths degree which sparked his interest in his future focus.

“In the third year we looked at the BSE crisis, and the fact that the human form of BSE was disproportionately seen in young males, who are also the demographic most likely to be eating low quality beef. We also looked at correlations between suicide rates and IQ level, both of the individual concerned and of their parents. Thanks to national service, Sweden had several generations worth of data, including IQ levels across generations of the same family. It was fascinating to see what questions that data could be used to answer.”

The discovery of the real-world applications statistics could be put to reignited Stephen’s interest in maths, and he completed a Masters with the same focus.

“People have been doing maths for thousands of years – maths research is hard because people have been doing it for so long! Statistics is newer, and driven by data and computation. The Sherlock Holmes side of it fascinates me; working out what the problem is as well as how to answer it.”

Following his Masters, Stephen worked with a Christian NGO in Russia, based with a Russian-led team in St Petersburg. That experience of the world beyond Cambridge and academia was crucial in establishing his career path.

“If I’d stepped straight from a BA to an MA to PhD, I don’t think I’d be as settled as I am.”

Stephen now specialises in Mendelian Randomisation, the use of genetic variants to understand the relationship between potential risk factors and particular disease outcomes. His work varies between projects which seek out the data to investigate specific questions, and those which make use of existing studies in order to explore something new.

“The disadvantage of the serendipitous approach is that you never quite answer the question you want to answer, you answer the one you’re able to. But often the data are more broadly applicable, so if we’ve done all the work for one disease, why not apply it to another disease?”

The availability of electronic health records has transformed the potential for investigations of this kind, with databases such as UK Biobank providing detailed information which can be applied to multiple queries.

During the past two years, the pandemic has led to multiple instances of biostatistics supplying valuable insights.

“We could see that there were questions that needed to be answered, and areas where we could help – for example by validating drug development. The use of (the immunosuppressive drug) Tocilizumab was one of these cases. Some people have a particular genetic variant which mimics the effect of the drug, and people with this variant have a lower risk of becoming ill with Covid-19. This finding was confirmed in randomised trials, and now the drug is licensed for use in Covid patients.”

As a mathematician whose work is so immersed in the medical world, Stephen laughs that he is always the person who knows either least or most about medicine in the room. But the inter-disciplinary nature of his work is a huge part of its appeal.

“Epidemiology straddles social sciences and hard science; human behaviour and biology. The use of face masks was a case in point – people’s behaviour changes when they are wearing them, which has an impact on studies into their efficacy. Genetics can’t be faked or mis-reported, but creativity is needed to find ways to use this information to answer relevant questions about how our choices affect our health.”