Grant: Project Grant

An estimated 670,000 Canadians suffer from heart failure (HF) with the estimated direct cost of management >$2.8B annually throughout Canada. There is no cure for HF and the only way to prevent death from HF is through early diagnosis and prevention, including lifestyle changes and drug treatment. Our research is focused on discovering the genes and proteins involved in HF to establish new ways to identify high-risk patients, modifiable risk factors, and preventive therapies. We will apply an innovative approach that will assess up to 358 blood proteins simultaneously from individuals with HF, and ultimately, we will leverage the strength of machine learning via multi-modal predictive models to develop a new approach to risk stratification for HF. It will use an individual's genomic, protein and echocardiogram data, as well as traditional clinical and cardio-metabolic risk factors to identify individuals at high risk of HF, before it becomes apparent, so early and effective preventative measures can be applied. Such an extensive approach has not been performed previously due to the need to access a large number of individuals specifically suffering from HF, and due to the vast analytical capabilities required to comprehensively analyze patients' blood proteins --something that our team is uniquely positioned to do. Technological advancements among our team, as well as the establishment of the 200,000 person cohort from the population (in whom we can study the development of new cases of HF in the community) and the Global Congestive Heart Failure (G-CHF) Study of 22,000 patients (in whom 3500 are carefully being characterised with detailed assessment of lifestyle factors, including diet, cardiac function, biomarkers and genes) -- which is the most comprehensive HF study worldwide, and with which the investigative team is integrally involved -- affords us unprecedented access to thousands of HF patient samples on which to perform the required analyses.