Scientist Profile Directory

Theme 1 focuses on epidemiology and genomics of poor outcomes in schizophrenia and other severe psychiatric disorders. Schizophrenia (SCZ) is one of the top 15 leading causes of disability worldwide, with the average number of life years lost ~30 years. Those with SCZ are at 15-25 times higher risk for suicide, compared to the general population. It is currently estimated that ~200,000 Canadians have SCZ. In 2004, the direct healthcare and non-healthcare costs related to SCZ in Canada were estimated at >$2B, and when considering additional losses, resulted in a total cost estimate of $6.85B. There are currently no means of predicting, at first clinical presentation, who will experience a poor outcome in SCZ. Our overall goal is early detection of those at high risk for poor outcomes in SCZ, thereby triggering logical and effective interventions to mitigate the personal, social, and societal costs associated with severe SCZ. Current or recent projects include an genetic assessment of treatment resistance or mortality in schizophrenia (published in Molecular Psychiatry and Translation Psychiatry). Project underway include GWAS of schizophrenia using Swedish cohorts (Sweden Schizophrenia Study), and a common variant genetic burden investigation of highly treatment resistant schizophrenia.

Theme 2 focuses on epidemiology and genomics of poor outcomes in multiple sclerosis (MS) and other chronic immunoinflammatory diseases. The prevention of poor outcomes, such as serious adverse drug reactions associated with MS therapies or the development of psychiatric disorders, is essential for those with MS and other chronic immunoinflammatory diseases. Currently, there are few clinically useful predictors of poor outcomes in MS. Findings from our cutting-edge work (published in Nature Genetics, Neurology, BMJ Open, Expert Opinion in Drug Safety, and MS and Related Disorders) could improve outcomes in MS and contribute to the future development of precision medicine approaches to MS and other autoimmune diseases. We have published work modelling longitudinal depressive symptoms to understand their evolution and identify any associated factors (including polygenic risk scores), Mendelian randomization to understand depression in MS and lastly a polygenic investigation of depression and anxiety in MS. Current work focuses on using polygenic scores to understand MS activity and progression.