Cortical Cell-Type-Specific, Layer-Specific, And Spatial Transcriptomic Signatures in Suicide Completers

Suicide is a complex polygenic disorder affecting millions of people worldwide. Multiple factors contribute to suicidal behaviors, including the environment, the genes that we inherit, and gene x environment interactions. Unfortunately, there are no established biological markers to predict suicidal behaviors. The reason behind this gap is that the neurobiology of suicide is not well understood. The genome-wide association studies predict that suicide is moderately heritable. However, the identification of causal disease mechanisms from these genetic studies remains a challenging task. Another approach for the identification of biological markers for suicidality is the bulk brain tissue transcriptomic data. However, bulk transcriptomic data dilute the cell-specific alterations, and it remains difficult to interpret whether the observed differences are by disease state or by differences in cell type composition between samples. Thus, cell-type-specific approaches are required to understand the neurobiology of a complex disorder like suicide. Both clinical and postmortem studies identified the dorsolateral prefrontal cortex (DLPFC) implicated in suicide. Human DLPFC consists of diverse cell classes (e.g., excitatory neurons, inhibitory neurons, astrocytes, microglia, oligodendrocytes, oligodendrocyte progenitor cells, endothelial cells, and others), and their functions and interactions differ in different spatial locations in DLPFC layers. We hypothesize that specific cell type(s) localized within the specific layer(s) of the dorsolateral prefrontal cortex are involved in suicide. We will use two cutting-edge techniques to address our hypothesis: single-nuclei RNA-Sequencing (snRNA-Seq) and multiplexed error-robust fluorescence in-situ hybridization (MERFISH). In aim (1), we will identify the specific cell type (s) affected by suicide within the DLPFC by performing snRNA-Seq on isolated nuclei from DLPFC. In addition, the suicide-associated gene expression signatures within the affected cell type (s) will be established. In aim (2), we will determine the DLPFC layer-specific whole-cell transcriptomes and identify the spatial context of the suicide-associated cell-type(s). In addition, the spatial context of individual dysregulated transcripts within each cell’s native environment will be resolved. Overall, our proposed research will identify cell-type-specific transcriptomic signatures of suicide which might serve as potential therapeutic targets for preventing suicide.