Grant: Banting Postdoctoral Fellowship Program

Analysis of postmortem brain tissue of depressed patients shows impairments in one specific cell type, but not others. The relative health of a cell is often reflected in the genes the cell is expressing. Differences in gene expression and cell function can also arise from normal variation in DNA (polymorphisms). We expect that some of this normal variability increases risk for depression even in healthy people. If we can identify this vulnerability early enough, we can intervene before the disorder develops. However, there is no easy way to assess the function of those cells in living humans. We propose a novel approach to do this indirectly. Based on postmortem brain tissue, we will create "polygenic risk scores" (PRS) to measure the contribution of multiple polymorphisms to variability in cell-specific gene expression. We will then compute the same PRS's in living individuals, for whom we also have magnetic resonance imaging (MRI) data on brain structure and function. We will examine how different cell-specific PRS correlate with the way different regions of the brain work together. We expect that the PRS for the cell type most impaired in depression will most strongly predict problematic brain activity or structural patterns. We will also conduct a parallel analysis in a mouse model of depression. Mice will have the same structural MRI data scans collected as humans, but their cell health will be measured directly in the brain using microscopy. We will then map MRI and cell health patterns onto each other and compare the results to those in humans, where cell health could only be measured indirectly. If we see similar results, this will give us confidence that our newly developed PRS's do measure cell health and can possibly help us quickly and non-invasively identify people with specific brain activity patterns that may put them at risk for depression. This will in turn create opportunities for early targeted intervention and prevention.