摘要：

We utilized a cell-level approach to examine glycolytic pathways in the DLPFC of subjects with schizophrenia (n?=?16) and control (n?=?16) and found decreased mRNA expression of glycolytic enzymes in pyramidal neurons, but not astrocytes. To replicate these novel bioenergetic findings, we probed independent datasets for bioenergetic targets and found similar abnormalities. Next, we used a novel strategy to build a schizophrenia bioenergetic profile by a tailored application of the Library of Integrated Network-Based Cellular Signatures data portal (iLINCS) and investigated connected cellular pathways, kinases, and transcription factors using Enrichr. Finally, with the goal of identifying drugs capable of “reversing” the bioenergetic schizophrenia signature, we performed a connectivity analysis with iLINCS and identified peroxisome proliferator-activated receptor (PPAR) agonists as promising therapeutic targets. We administered a PPAR agonist to the GluN1 knockdown model of schizophrenia and found it improved long-term memory. Taken together, our findings suggest that tailored bioinformatics approaches, coupled with the LINCS library of transcriptional signatures of chemical and genetic perturbagens, may be employed to identify novel treatment strategies for schizophrenia and related diseases.

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