Trying to predict who is at risk for disease
Revealing a scientific story and a musical phrase are equally fascinating. During the day, I unravel the story of how exposure to air pollution and other environmental exposures lead to chronic diseases such as lung disease, and in my spare time, I make music on my drums and piano. It’s easy to take data or musical notes and put them in a table or on a sheet of paper – the magic comes in making sense of them such that others, too, can soak up the impact.
I’m diving into molecular epidemiology and looking for molecular markers that can help us calculate the probability of disease.
Studying risk factors
Non-genetic risk factors are becoming more prominent in health research. These include environmental factors, like climate, air pollution and chemical toxicants, and lifestyle choices, such as inactivity and cigarette smoking.
Utrecht University and the UMC Utrecht participate in one of the largest projects in the world focusing on such variables. The EPIC Study (European Prospective Investigation into Cancer and Nutrition) has, since the 1990s, enrolled more than half-a-million subjects to unravel both the genetic and non-genetic causes of disease.
The prospect of being able to predict, and perhaps prevent, the onset of disease is enticing. Can we develop methods sensitive enough to predict how environmental factors increase our chances of becoming ill?
Air pollution at the molecular level
Take, for example, air pollution. We know that it can play a role in lung disease. By studying patterns within a population – of exposure, of disease manifestation and progression, of gene behavior – we may be able to predict who is at high risk for lung disease and why. In order to do this, I’m diving into molecular epidemiology and looking for molecular markers that can help us calculate the probability of disease.
A new concept, called the exposome, is poised to provide a wealth of information on how our environment can influence health.
Similar to how the era of genomics has quickly advanced our understanding of population genetics and diseases, a new concept, called the exposome, is poised to provide a wealth of information on how our environment can influence health. The amount of data we need is astonishing, as it takes a lifetime of exposure to build up to a disease. Right now, we can now only look at a snapshot of how our biological system changes. We study one or multiple risk factors at a time and figure out which biological pathway is affected, and whether those perturbations result in disease.
Yet, for a single moment in time, we can amass an incredible amount of information. Our latest study on air pollution includes omics data (epigenomics, transcriptomics, proteomics, metabolomics), and taken together, we can see, at a certain point in a person’s life, how air pollution affects gene expression, proteins and cell behavior. Comparing this to other studies, we hope to find commonalities and patterns within a population. Perhaps then, we can predict who is at high risk for disease.
Genetic and non-genetic information tells your story
One of the greatest challenges in this field is how to interpret our data. In our study, we’ve found known immune markers for asthma and lung cancer, which tells us that our methods are on the right track. We’ve also identified new biomarkers, which is great, but what do they mean? This is the part I enjoy the most: when the statistical analyses are done and I have results, I get to interpret the information and try and unravel the story behind it.
- Email: email@example.comPhone: 030 253 5372Associate ProfessorVeterinary Medicine - Department Population Health Sciences - Institute for Risk Assessment Sciences (IRAS) - One Health Epidemiology Chemical Agents