3 November 2022

"Integrating epidemiological and omics data can help us to understand what's really going on"


Associate Professor Marta Guasch-Ferré relocates from Harvard T.H. Chan School of Public Health, Boston, to start a new Group focused on nutrition and metabolism, which will straddle CBMR and the Department of Public Health at the University of Copenhagen.

A portrait of Marta Guasch-Ferré

Associate Professor Marta Guasch-Ferré was born and raised in Catalonia, Spain, and completed her undergraduate studies and PhD in nutrition and metabolism at the Rovira i Virgili University and University of Barcelona. In 2015 she relocated to the Department of Nutrition, Harvard T.H. Chan School of Public Health (Boston, USA) for a Postdoctoral Fellowship, and where she most recently assumed the role of Senior Research Scientist in 2021. Since 2018, she also worked as Instructor of Medicine and Associate Epidemiologist at Harvard Medical School (Boston, USA).

She joins CBMR in a joint position with the Department of Public Health, where she will continue her research that incorporates high-throughput –omics techniques, metabolomics and genetics, into traditional epidemiological analysis to gain insights into underlying mechanisms that could explain the associations between diet and lifestyle factors in relation to cardiovascular disease and type 2 diabetes.

We sat down with Marta to learn a little more about her background and the origins of her scientific interests.

Have you always wanted to be a scientist?

I think my main interest in science started way back in high school when I did my final project in high school on obesity. I learned how diet plays a role in the disease, and that it was possible to study nutrition. This led me to want to work in the clinic as a nutritionist and help people with different diseases. I was very drawn to directly helping patients through interventions to change their dietary habits. But then I learned that there are other ways of doing science, for example through epidemiology or clinical trials and big cohort studies and I liked that.

At what point did you start to recognize the potential for big data approaches in your epidemiological research?

My doctoral thesis was mainly related at looking at the Mediterranean diet, which is a very well-known dietary pattern in relation to reducing the risk of cardiovascular diseases. But while we recognized this association, we didn’t understand the underlying biological mechanisms. So, when I started my Postdoc at Harvard, we thought that incorporating omics data and big data, specifically metabolomics, could help identify some of the potential mechanisms as well as potential biomarkers of disease, especially in the years before the diagnosis.

Many of the scientists at CBMR are working toward developing new therapies to treat cardiometabolic diseases. How do you hope to make an impact?

Most of my research has been helping to build evidence for public health messaging on dietary guidelines, for example. There are so many factors at play that it’s difficult to puzzle it all together. Basic research offers many insights as to what’s going on inside the body, but we also need complementary work such as large cohort studies or clinical trials to bridge the gap to populations, which will improve public health messaging. General public health messages work well for a huge majority of the population. Some advice applies to everyone, for example sugary beverages are bad for everyone in excess, so is smoking. But there are other issues you cannot address with public health messaging, for example targeted interventions to particular populations with a higher risk of diseases. So public health messages are complementary to precision health approaches.

What we are working hard on is identifying more objective biomarkers of diet. Many cohort studies require participants to self-report and there are many problems associated with the reliability of this information – you may over or underestimate your food intake, activity levels, or sleep, for example. So, we are looking at devices that can quickly provide accurate data on what people are really doing. Integrating epidemiological data, metabolomics, genetics, and microbiome data can help us find objective biomarkers that tell us what’s really going on, and associations with rates of cardiovascular disease, for example.

My Group will also look at the intersection between planetary health and human health, by identifying diets that are both good for our health and sustainable for our planet. This is a very important line of research that I'm very excited to investigate further because the pressure on resources with a growing human population.