The disruption of brain energy metabolism, leading to alterations in synaptic signaling, neural circuitry, and neuroplasticity, has been implicated in severe mental illnesses such as schizophrenia, bipolar disorder, and major depressive disorder. The therapeutic potential of ketogenic interventions in these disorders suggests a link between metabolic disturbances and disease pathology; however, the precise mechanisms underlying these metabolic disturbances, and the therapeutic effects of metabolic ketogenic therapy, remain poorly understood. In this study, we conducted an in silico analysis of transcriptomic data to investigate perturbations in metabolic pathways in the brain across severe mental illnesses via gene expression profiling. We also examined dysregulation of the same pathways in rodent or cell culture models of ketosis, comparing these expression profiles to those observed in the disease states. Our analysis revealed significant perturbations across all metabolic pathways, with the greatest perturbations in glycolysis, the tricarboxylic acid (TCA) cycle, and the electron transport chain (ETC) across all three disorders. Additionally, we observed some discordant gene expression patterns between disease states and ketogenic intervention studies, suggesting a potential role for ketone bodies in modulating pathogenic metabolic changes. Our findings highlight the importance of understanding metabolic dysregulation in severe mental illnesses and the potential therapeutic benefits of ketogenic interventions in restoring metabolic homeostasis. This study provides insights into the complex relationship between metabolism and neuropsychiatric disorders and lays the foundation for further experimental investigations aimed at appreciating the implications of the present transcriptomic findings as well as developing targeted therapeutic strategies.

Gene expression alterations in postmortem schizophrenia tissue are well-documented and are influenced by genetic, medication, and epigenetic factors. The Wingless/Integrated (WNT) signaling pathway, critical for cell growth and development, is involved in various cellular processes including neurodevelopment and synaptic plasticity. Despite its importance, WNT signaling remains understudied in schizophrenia, a disorder characterized by metabolic and bioenergetic defects in cortical regions. In this study, we examined the gene expression of 10 key WNT signaling pathway transcripts: IQGAP1, CTNNβ1, GSK3β, FOXO1, LRP6, MGEA5, TCF4, βTRC, PPP1Cβ, and DVL2 in the dorsolateral prefrontal cortex (DLPFC) using postmortem tissue from schizophrenia subjects (n = 20, 10 males, 10 females) compared to age, pH, and postmortem interval (PMI)-matched controls (n = 20, 10 males, 10 females). Employing the R-shiny application Kaleidoscope, we conducted in silico “lookup” studies from published transcriptomic datasets to examine cell- and region-level expression of these WNT genes. In addition, we investigated the impact of antipsychotics on the mRNA expression of the WNT genes of interest in rodent brain transcriptomic datasets. Our findings revealed no significant changes in region-level WNT transcript expression; however, analyses of previously published cell-level datasets indicated alterations in WNT transcript expression and antipsychotic-specific modulation of certain genes. These results suggest that WNT signaling transcripts may be variably expressed at the cellular level and influenced by antipsychotic treatment, providing novel insights into the role of WNT signaling in the pathophysiology of schizophrenia.

The disruption of brain energy metabolism, leading to alterations in synaptic signaling, neural circuitry, and neuroplasticity, has been implicated in severe mental illnesses such as schizophrenia, bipolar disorder, and major depressive disorder. The therapeutic potential of ketogenic interventions in these disorders suggests a link between metabolic disturbances and disease pathology; however, the precise mechanisms underlying these metabolic disturbances and the therapeutic effects of metabolic ketogenic therapy remain poorly understood. In this study, we conducted an in silico analysis of transcriptomic data to investigate perturbations in metabolic pathways in the brain across severe mental illnesses via gene expression profiling. We also examined dysregulation of the same pathways in rodent or cell culture models of ketosis, comparing these expression profiles to those observed in the disease states. Our analysis revealed significant perturbations across all metabolic pathways, with the greatest perturbations in glycolysis, the tricarboxylic acid (TCA) cycle, and the electron transport chain (ETC) across all three disorders. Additionally, we observed some discordant gene expression patterns between disease states and ketogenic intervention studies, suggesting a potential role for ketone bodies in modulating pathogenic metabolic changes. Our findings highlight the importance of understanding metabolic dysregulation in severe mental illnesses and the potential therapeutic benefits of ketogenic interventions in restoring metabolic homeostasis. This study provides insights into the complex relationship between metabolism and neuropsychiatric disorders and lays the foundation for further experimental investigations aimed at appreciating the implications of the present transcriptomic findings as well as developing targeted therapeutic strategies.