Innovations statistiques pour l'identification de facteurs de risques génétiques et reliés au mode de vie pour les maladies cardiométaboliques

 

Marie-Pierre Sylvestre

Centre de recherche de l'Institut de cardiologie de Montréal

 

Domaine :  santé des populations

Programme chercheurs-boursiers - Junior 1

Concours 2017-2018

Cardiometabolic diseases such as diabetes and hypertension are among the diseases with the largest burden in terms in terms of mortality, quality of life and health costs. However, a significant proportion of these diseases can be prevented, which is a key issue of public health. Evidence shows that both genetic factors as well as factors related to lifestyle, such as smoking and diet, influence the development of cardiometabolic diseases. The questions that my research proposal addresses are: why and how do selected individuals develop cardiometabolic disease? Answers to these questions will improve our understanding of these diseases, but also provide tools for the early detection of individuals at risk. This can lead to the development of strategies to prevent the onset of cardiometabolic disease and accelerate the progress of personalised medicine, which involves the development of targeted treatment based on the genetic makeup of a patient.

A major roadblock in this endeavour concerns current analytical skills. Indeed, because of recent advances in technology, bigger, richer and more complex datasets including genetic information, medical histories and life-style related habits are constantly being assembled and can be used to address these questions. However, currently available statistical methods are not sophisticated enough to handle the complexity of these dataset, which reduces our ability to make new discoveries. This research program proposes novel statistical methods that fully exploit the complexity of data and have the potential to uncover undetected factors increasing the likelihood of developing cardiometabolic disease.