Deconvolution of transcriptional networks identifies TCF4 as a master regulator in schizophrenia

Applying tissue-specific deconvolution of transcriptional networks to identify their master regulators (MRs) in neuropsychiatric disorders has been largely unexplored. Here, using two schizophrenia (SCZ) case-control RNA-seq datasets, one on postmortem dorsolateral prefrontal cortex (DLPFC) and another on cultured olfactory neuroepithelium, we deconvolved the transcriptional networks and identified as a top candidate MR that may be dysregulated in SCZ. We validated as a MR through enrichment analysis of -binding sites in induced pluripotent stem cell (hiPSC)-derived neurons and in neuroblastoma cells. We further validated the predicted targets by knocking down in hiPSC-derived neural progenitor cells (NPCs) and glutamatergic neurons (Glut_Ns). The perturbed gene network in NPCs was more enriched for pathways involved in neuronal activity and SCZ-associated risk genes, compared to Glut_Ns. Our results suggest that may serve as a MR of a gene network dysregulated in SCZ at early stages of neurodevelopment.