Phosphoinositides (PIs) play important roles in the structure and function of the brain. Associations between PIs and the pathophysiology of schizophrenia have been studied. However, the significance of the PI metabolic pathway in the pathology of schizophrenia is unknown. We examined the expression of PI signaling-associated proteins in the postmortem brain of schizophrenia patients. Protein expression levels of phosphatidylinositol 4-phosphate 5-kinase type-1 gamma (PIP5K1C), phosphatidylinositol 4-kinase alpha (PIK4CA, also known as PIK4A), phosphatase and tensin homolog deleted from chromosome 10 (PTEN), protein kinase B (Akt), and glycogen synthase kinase 3β (GSK3β) were measured using enzyme-linked immunosorbent assays and multiplex fluorescent bead-based immunoassays of the prefrontal cortex (PFC) of postmortem samples from 23 schizophrenia patients and 47 normal controls. We also examined the association between PIK4CA expression and its genetic variants in the same brain samples. PIK4CA expression was lower, whereas Akt expression was higher, in the PFC of schizophrenia patients than in that of controls; PIP5K1C, PTEN, and GSK3β expression was not different. No single-nucleotide polymorphism significantly affected protein expression. We identified molecules involved in the pathology of schizophrenia via this lipid metabolic pathway. These results suggest that PIK4CA is involved in the mechanism underlying the pathogenesis of schizophrenia and is a potential novel therapeutic target.

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BackgroundEvaluating and controlling confounders are necessary when investigating molecular pathogenesis using human postmortem brain tissue. Particularly, tissue pH and RNA integrity number (RIN) are valuable indicators for controlling confounders. However, the influences of these indicators on the expression of each gene in postmortem brain have not been fully investigated. Therefore, we aimed to assess these effects on gene expressions of human brain samples.MethodsWe isolated total RNA from occipital lobes of 13 patients with schizophrenia and measured the RIN and tissue pH. Gene expression was analyzed and gene sets affected by tissue pH and RIN were identified. Moreover, we examined the functions of these genes by enrichment analysis and upstream regulator analysis.ResultsWe identified 2,043 genes (24.7%) whose expressions were highly correlated with pH; 3,004 genes (36.3%) whose expressions were highly correlated with RIN; and 1,293 genes (15.6%) whose expressions were highly correlated with both pH and RIN. Genes commonly affected by tissue pH and RIN were highly associated with energy production and the immune system. In addition, genes uniquely affected by tissue pH were highly associated with the cell cycle, whereas those uniquely affected by RIN were highly associated with RNA processing.ConclusionThe current study elucidated the influence of pH and RIN on gene expression profiling and identified gene sets whose expressions were affected by tissue pH or RIN. These findings would be helpful in the control of confounders for future postmortem brain studies.

Schizophrenia is a multifactorial disorder, the genetic architecture of which remains unclear. Although many studies have examined the etiology of schizophrenia, the gene sets that contribute to its symptoms have not been fully investigated. In this study, we aimed to identify each gene set associated with corresponding symptoms of schizophrenia using the postmortem brains of 26 patients with schizophrenia and 51 controls. We classified genes expressed in the prefrontal cortex (analyzed by RNA-seq) into several modules by weighted gene co-expression network analysis (WGCNA) and examined the correlation between module expression and clinical characteristics. In addition, we calculated the polygenic risk score (PRS) for schizophrenia from Japanese genome-wide association studies, and investigated the association between the identified gene modules and PRS to evaluate whether genetic background affected gene expression. Finally, we conducted pathway analysis and upstream analysis using Ingenuity Pathway Analysis to clarify the functions and upstream regulators of symptom-related gene modules. As a result, three gene modules generated by WGCNA were significantly correlated with clinical characteristics, and one of these showed a significant association with PRS. Genes belonging to the transcriptional module associated with PRS significantly overlapped with signaling pathways of multiple sclerosis, neuroinflammation, and opioid use, suggesting that these pathways may also be profoundly implicated in schizophrenia. Upstream analysis indicated that genes in the detected module were profoundly regulated by lipopolysaccharides and CREB. This study identified schizophrenia symptom-related gene sets and their upstream regulators, revealing aspects of the pathophysiology of schizophrenia and identifying potential therapeutic targets.