Marc-André Legault, new professor at the Faculty of Pharmacy at the University of Montreal, aims to better understand the influence of genetic variations on response to drugs in order to transform health care. By combining genetic statistics, genetic epidemiology and machine learning, it seeks to designate patients most likely to benefit from specific treatments while minimizing their side effects. Research that could transform personalized medicine.
An injection for research from the first year of university
It was at the end of his first year of a bachelor’s degree in biomedical sciences that Marc-André Legault fell in love with research. He completed an internship at the School of Optometry at the University of Montreal and joined a neuroscience laboratory, an experience that left a lasting impression on him. He carried out his first real research project there and he devoted himself to it with passion. “I was really able to carry out my research project through experiments, report the results, interact with the rest of the team,” he remembers enthusiastically.
Then a significant meeting with a bioinformatics researcher redefined his trajectory. “He told me to what extent bioinformatics was an emerging discipline and that it was very useful in biomedical research in order to solve concrete problems,” he recalls. Fascinated by the potential of this discipline that he could combine with his curiosity for new technologies, the student decided to specialize in bioinformatics.
During his studies, he joined the staff of Marie-Pierre Dubé’s laboratory at the Montreal Heart Institute. There, he was able to develop his skills in the development of bioinformatics tools, focusing in particular on the comparison of methods for detecting structural variations of the genome. It was also there that he co-signed his first scientific publication, an innovative work for which he used monozygotic twins to compare different algorithms for detecting genetic variations.
Predicting drug efficacy using omics approaches
Marc-André Legault explores cutting-edge approaches in pharmaco-omics to transform personalized medicine. Rather than being limited to the analysis of a single gene or a single protein, it adopts a more global vision, taking into account all the molecules present in the body. “In genetic epidemiology, we focus on simple biomarkers such as cholesterol levels to assess the risks of cardiovascular diseases. With omics approaches, we analyze the effect of drugs on all proteins in the body,” he explains.
In his doctorate, Marc-André Legault analyzed the effects of 26,616 proteins on 1746 phenotypes based on data from more than 413,000 individuals from the UK Biobank, a large population cohort in the United Kingdom. This research, accessible via the ExPheWAS platform, allows us to better understand the links between genetic variations and different diseases.
With this work, the professor aims to provide a complete molecular picture of patients’ health status by integrating data on proteins and other biomarkers. This approach will ultimately make it possible to select the medications most suited to each individual, taking into account their unique biological profile. “We can then use this information to prioritize treatments, personalizing drug choices based on the patient’s current condition,” explains the professor.
A key aspect of his research involves modeling the effect of drugs on people who don’t take them, using their genetic variations. “If a person carries a genetic variation that naturally reduces the activity of an enzyme, this can mimic the effect of a drug designed to inhibit that enzyme,” he says. These models thus prove useful in the development of drugs to help the development of clinical studies or to predict the long-term effects of the use of drugs.
As an associated researcher at Mila, the Quebec Institute of Artificial Intelligence, Marc-André Legault continues to design bioinformatics tools and machine learning algorithms to analyze the consequences of genetic variations on responses to treatments. His research also includes “drug repurposing,” or the use of existing treatments for other diseases. For example, a drug designed to treat Crohn’s disease could be repurposed to treat arthritis after studying its effects on patients’ omics profiles.
Research for children
Marc-André Legault is now a researcher at the Azrieli Research Center at CHU Sainte-Justine, where he works to determine which medications prescribed to adults could be prescribed to children. This presents a major challenge for researchers accustomed to using supercomputers and big data banks: “In adults, it is common to have cohorts of more than 500,000 or 1,000,000 participants; in children, it is extremely rare,” he says.
“Understanding at the molecular level the effect of drugs in children will allow us to focus on treatments adapted to their specific needs,” he continues, determined to improve care for young patients.
Transmit passion for research
Alongside his research activities, Marc-André Legault takes pleasure in passing on his knowledge to his classes at the University of Montreal. This winter, he will teach them Mendelian randomization, which is closely linked to his research work. “Teaching fuels research, and I hope to communicate this passion to my students,” he confides. For him, the greatest reward would be to see a student inspired by his courses join his laboratory team, ready to contribute to research and carry out their own innovative projects.
