Registration of spatial gene expression in key nodes of reward-related circuitry in the human brain

PROJECT SUMMARY Drug addiction is highly comorbid with psychiatric disorders, particularly post-traumatic stress disorder (PTSD) and major depressive disorder (MDD). These conditions share underlying genetic risk and are exacerbated by similar environmental factors, including exposure to stress and traumatic events. The dorsal anterior cingulate cortex (dACC), nucleus accumbens (NAc) and amygdala constitute key nodes of the brain’s reward circuitry, and perturbations in reward signaling are highly implicated in addiction, MDD and PTSD. The human dACC, NAc and amygdala have unique neuroanatomical features, which correspond to distinct biological functions. Given the close relationship between brain structure and function, precisely assigning gene expression to the spatial coordinates of individual cell populations within the cytoarchitecture can significantly advance our understanding of how dysregulation in these areas contributes to addiction and comorbid neuropsychiatric disorders. Towards this goal, we propose to generate detailed spatial transcriptomic maps, which will be combined with single-nucleus RNA sequencing (snRNA-seq) to register molecularly-defined cell types to their spatial coordinates, facilitating prediction of the anatomical locations of distinct neuronal classes of cells within the dACC, NAc and amygdala. These molecularly- and spatially-defined populations of cells will be associated with gene expression changes linked to substance use and comorbid neuropsychiatric disorders. We hypothesize that these regions have a precise molecular architecture that reveals 1) topographically organized and molecularly-defined cell types within layers of the dACC, and across sub-regions of the NAc and amygdala; 2) spatial-enrichment of genes associated with addiction and comorbid neuropsychiatric disorders. By generating the first transcriptome-scale spatial maps of the human dACC, NAc and amygdala, critical information about the molecular landscape of these regions within the architecture of the human brain will be generated. Our spatial registration approach will facilitate refined annotation of cell types in the human brain, and contribute to understanding addiction and comorbid neuropsychiatric disorders by identifying clinical associations with molecularly- and spatially-defined cell populations that can be targeted for prevention and treatment.