The researchers demonstrated that mimicking a de novo mutation of the schizophrenia-risk gene SETD1A in mice induced various abnormal behaviors relevant to schizophrenia. Setd1a in postsynaptic neurons positively regulates excitatory synaptic transmission and structure in the medial prefrontal cortex through histone modification and regulating the expression of diverse synaptic genes.

Direct and indirect pathway medium-sized spiny neurons (dMSNs and iMSNs) in the neostriatum were selectively labeled with green and red fluorescent proteins by an AAV vector. Both pathways formed two axonal arborizations in the globus pallidus external segment, and dMSN axons converged in the center of iMSN projection fields.

The researchers developed a simplified method for the production of AAV vectors, which drastically shortens the purification time from 1.5 days to 2 – 4 h. Systemic infusion of AAV-PHP.eB prepared using this method transduced whole brain. Transduction efficacy is comparable to the conventional method.

A machine learning classifier using neuroimaging data in schizophrenia, autism, and healthy controls classifies people with ultra-high risk and first episode psychosis into schizophrenia or healthy controls, but not autism.