Identifying cortical circuit changes in Akap11 mutant mice

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Project Summary/Abstract A major barrier towards developing effective therapeutics for psychiatric diseases like schizophrenia (SCZ) and bipolar disorder (BD) is the lack of a clear underlying neurobiological mechanism. Multiple lines of evidence from human studies and post-mortem tissue implicate changes to the cortical circuit, including cell-type composition and local and long-range synaptic connectivity. However, this hypothesis has been difficult to test directly due to a lack of tools to carry out systematic and unbiased analyses of cortical circuitry a lack of strong genetic risk factors that can be modeled in mice and. In this proposal, we will develop standardized methods to measure the cortical circuit using spatial transcriptomics combined with viral synaptic tracing. We will apply this method to genes identified by recent, large-scale exome sequencing studies that have identified rare loss-of- function mutations strongly associated with disease. Among those genes implicated in both BD and SCZ is Akap11, whose gene product regulates PKA, a central signaling molecule that controls neuronal transcription and plasticity, and GSK3β, the proposed target of lithium treatment in BD. We will use multiplexed error-robust fluorescent in situ hybridization (merFISH) to classify the transcriptional identity of cortical cells and their laminar distribution and how they are altered in Akap11 mutant mice (Aim 1). We will also optimize conditions for both long-range and local synaptic tracing using replication-defective rabies viruses to explore alterations to synaptic connectivity in Akap11 mutant mice (Aim 2). Local labeling of synaptic inputs with rabies will be combined with merFISH-based to identify cell-type specific changes in connectivity. These experiments will identify changes in cellular composition and connectivity caused by loss of Akap11 and generate hypotheses on the circuit mechanisms underlying disease. Importantly, this proposal will also establish an analysis pipeline for characterizing the cortical circuit that can be applied across many disease-associated variants. Future studies using this pipeline will identify convergent circuit mechanisms across high-confidence risk factors that are most likely to cause disease and provide promising targets for new therapies.