Prefrontal co-expression of schizophrenia risk genes is associated with treatment response in patients

Abstract

Gene co-expression networks are relevant to functional and clinical translation of schizophrenia (SCZ) risk genes. We hypothesized that SCZ risk genes may converge into coexpression pathways which may be associated with gene regulation mechanisms and with response to treatment in patients with SCZ. We identified gene co-expression networks in two prefrontal cortex post-mortem RNA sequencing datasets (total N=688) and replicated them in four more datasets (total N=227). We identified and replicated (all p-values<.001) a single module enriched for SCZ risk loci (13 risk genes in 10 loci). In silico screening of potential regulators of the SCZ risk module via bioinformatic analyses identified two transcription factors and three miRNAs associated with the risk module. To translate post-mortem information into clinical phenotypes, we identified polymorphisms predicting co-expression and combined them to obtain an index approximating module co-expression (Polygenic Co-expression Index: PCI). The PCI-co-expression association was successfully replicated in two independent brain transcriptome datasets (total N=131; all p-values<.05). Finally, we tested the association between the PCI and short-term treatment response in two independent samples of patients with SCZ treated with olanzapine (total N=167). The PCI was associated with treatment response in the positive symptom domain in both clinical cohorts (all p-values<.05).In summary, our findings in a large sample of human post-mortem prefrontal cortex show that coexpression of a set of genes enriched for schizophrenia risk genes is relevant to treatment response. This co-expression pathway may be co-regulated by transcription factors and miRNA associated with it.

Brain network dynamics during working memory are modulated by dopamine and diminished in schizophrenia

“…Polygenic co-expression index calculation. Recent publications have shown that gene sets defined using co-expression networks and selected for their association with the genes DRD1 and DRD2 provided replicable predictions of n-back-related brain activity and behavioral indices in line with the role of prefrontal dopamine in working memory 27,[88][89][90] . The gene sets have been previously identified using weighted Gene Co-expression Network Analysis [WGCNA 28 ] applied on the Braincloud dataset (N = 199) of post-mortem DLPFC gene expression 29 resulting in 67 non-overlapping sets of genes based on their expression pattern.…”

Brain state stability during working memory is explained by network control theory, modulated by dopamine D1/D2 receptor function, and diminished in schizophrenia

“…Previous publications have shown that gene sets defined using co-expression networks and selected for their association with the genes DRD1 and DRD2 provided replicable predictions of n-back-related brain activity and behavioral indices (23,(25)(26)(27). Weighted Gene Co-expression Network Analysis [WGCNA (28)] applied on the Braincloud dataset (N=199) of post-mortem DLPFC gene expression ( 29) identified 67 nonoverlapping sets of genes based on their expression pattern.…”