Grant: CIHR Fellowship

Depression is a serious mental condition which affects individuals of all ages, and with more women affected than men. According to WHO rankings, depression is the fourth leading factor of disability worldwide. As a result, depression also poses a significant burden to healthcare systems. Although there are numerous antidepressant drugs available, finding the right medication for the right patient has remained challenging. It is known that depression and drug response are genetically mediated, however, more research is needed using well-characterized samples. A confounding factor has been that a large proportion of depressed patients respond to placebo, but placebo effects have remained understudied with only a few genetic studies conducted. My research aims to evaluate computational models that will be used to predict which patients are likely to respond to treatment by investigating genomic DNA, clinical, and demographic characteristics. To achieve this goal, I will use a large and well-characterized sample composed of 450 individuals treated with an antidepressant or placebo. I will use the most advanced computational models to develop algorithms that will predict response to either treatment. The proposed study is part of the larger CAN-BIND (Canadian Biomarker Integration Network in Depression) program. In addition, I have access to a second large and well-characterized cohort of patients treated for late-life depression, which will serve as my independent sample and independent placebo-treated sample (n=257). The proposed work has the potential to significantly broaden our knowledge on the genetics of treatment response in depression. Detailed knowledge about genetic determinants of drug response represents the first steps towards personalized medicine and tailored treatment for individual patients.