Association of astrocyte-specific gene expression in the dorsolateral prefrontal cortex with treatment-resistant schizophrenia

Abstract

Abstract Treatment-resistant schizophrenia (TRS) is defined as the absence of symptomatic response to two different adequately administered antipsychotic drugs other than clozapine, which is the most effective drug in these patients. Gene expression profiling studies could be a valuable tool in identifying the specific genes and pathways involved in the mechanism of action of clozapine, leading to a better understanding of the molecular biology underlying TRS. We analyzed gene co-expression modules (clusters of genes with highly correlated expression) in the dorsolateral prefrontal cortex (DLPFC) of postmortem brains from patients with schizophrenia and healthy controls. We aimed to identify the co-expressed modules that reflect the genetic differences between clozapine-treated and non-clozapine-treated patients with schizophrenia as a proxy of TRS. Gene expression of DLPFC samples from 26 subjects with schizophrenia (13 clozapine treated and 13 non-clozapine treated) were analyzed using Clariom S Human Array. Raw gene expression data from 37 healthy controls was downloaded from the GSE92538 datasets. Weighted gene co-expression network analysis (WGCNA) was applied to identify modules of co-expressed genes and to test its association with clozapine treatment using a test for interaction. As a result of our analysis of the gene co-expression architecture in the DLPFC, among the 13 modules identified, one module (green) was significantly associated with clozapine treatment. This module was significantly enriched in astrocyte markers and genes involved in the polygenic architecture of TRS. This finding provides cell type-specific associations that could help in the interpretation of the neurobiological basis of TRS. A better understanding of the specific DLPFC cell types involved in TRS will contribute to the study of potential pathways and ultimately help improve psychiatric classification tools in personalized medicine.