Analysis of gene co-expression connectivity dynamics implicates aberrant neuron-oligodendroglia interactions in schizophrenia

Abstract

Dysconnectivity in schizophrenia is a pervasive concept across various levels of systems biology. To better understand disrupted patterns of molecular connectivity in schizophrenia, we apply innovative approaches to gene co-expression networks starting from multiple regions of postmortem brain (bulk RNA-Seq from dorso-lateral prefrontal cortex- (DLPFC) (Ndonors=297; sex: M/F = 212/85), hippocampus (Ndonors=250; sex: M/F = 181/69) and caudate (Ndonors=349; sex: M/F = 242/107). Here we identify differentially connected genes (DCG) in schizophrenia networks that deviate from architectural relationships characteristic of neurotypical gene networks based on three network metrics- total connectivity (kTot), clustering coefficient (C), and intra-module degree (kIn). We find multiple DCG consistent across all brain regions, most of which we then independently confirm in brain single nuclei (snRNAseq) data and in four independent human iPSC-derived brain organoids. DCG specific for each network parameter shows enrichment in schizophrenia genetic signal, in pathways prominently related to neurons and oligodendroglia functionality, and in cell-type specific co-expression patterns that differ between neurotypical and schizophrenia, implicating neuronal-oligodendroglia incoordination. WGCNA provides insight into which genes belong to a network. Here, the authors propose a refined approach to define dynamic gene relationships, able to identify aberrant neuron-oligodendroglia interactions when applied to the study of schizophrenia.