Mechanism of electroconvulsive therapy in schizophrenia: a bioinformatics analysis study of RNA-seq data.

OBJECTIVE: The molecular mechanism of electroconvulsive therapy (ECT) for schizophrenia remains unclear. The aim of this study was to uncover the underlying biological mechanisms of ECT in the treatment of schizophrenia using a transcriptional dataset. METHODS: The peripheral blood mRNA sequencing data of eight patients (before and after ECT) and eight healthy controls were analyzed by integrated co-expression network analysis and the differentially expressed genes were analyzed by cluster analysis. Gene set overlap analysis was performed using the hypergeometric distribution of phypfunction in R. Associations of these gene sets with psychiatric disorders were explored. Tissue-specific enrichment analysis, gene ontology enrichment analysis, and protein-protein interaction enrichment analysis were used for gene set organization localization and pathway analysis. RESULTS: We found the genes of the green-yellow module were significantly associated with the effect of ECT treatment and the common gene variants of schizophrenia ( P  = 0.0061; family-wise error correction). The genes of the green-yellow module are mainly enriched in brain tissue and mainly involved in the pathways of neurotrophin, mitogen-activated protein kinase and long-term potentiation. CONCLUSION: Genes associated with the efficacy of ECT were predominantly enriched in neurotrophin, mitogen-activated protein kinase and long-term potentiation signaling pathways.

Electroconvulsive Therapy Reduces Protein Expression Level of EP300 and Improves Psychiatric Symptoms and Disturbance of Thought in Patients with Schizophrenia.

Objective: Although electroconvulsive therapy (ECT) has been employed as an effective treatment strategy and to improve mental symptoms in schizophrenia (SCZ), its action mechanisms remain unclear. Our previous study found that some genes and biological pathways were closely related to ECT through genetic technology analysis, such as LTP pathway and EP300. This study combined with healthy controls and symptomatology analysis to further explore the changes of expression of EP300 protein in treatment and related symptoms of SCZ. Methods: One hundred and one patients with SCZ and 45 healthy controls (HCs) were enrolled in this study. Patients with SCZ received acute courses of 6 times bilateral ECT. The peripheral blood of patients with SCZ (BECT: before ECT; AECT: after ECT) and the HCs was collected to calculate the changes of expression level of EP300 protein by enzyme-linked immunosorbent assay. The Positive and Negative Symptoms Scale (PANSS) was used to evaluate the severity of symptoms of SCZ patients and the efficiency of the ECT. Results: There was a statistical difference of EP300 protein expression in patients with SCZ (BECT and AECT) (F = 114.5, p < 0.05). ECT reduced plasma expression level of EP300 protein in patients with SCZ, which was not statistically different from that in HCs (t = 4.47, p = 0.20). The change of the expression level of EP300 protein in patients with SCZ (BECT and AECT) has a positive correlation with reduction rate of positive symptoms (r = 0.228, p < 0.05) and disturbance of thought (r = 0.219, p < 0.05). Conclusion: Our study suggests that the expression level of EP300 protein has a significant change in patients with SCZ treating with ECT, and EP300 may have some connections with positive symptoms and disturbance thought of patients with SCZ.

Transcriptome Sequencing Reveals the Potential Mechanisms of Modified Electroconvulsive Therapy in Schizophrenia.

OBJECTIVE: Schizophrenia (SCZ) is one of the most common and severe mental disorders. Modified electroconvulsive therapy (MECT) is the most effective therapy for all kinds of SCZ, and the underlying molecular mechanism remains unclear. This study is aim to detect the molecule mechanism by constructing the transcriptome dataset from SCZ patients treated with MECT and health controls (HCs). METHODS: Transcriptome sequencing was performed on blood samples of 8 SCZ (BECT: before MECT; AECT: after MECT) and 8 HCs, weighted gene co-expression network analysis (WGCNA) was used to cluster the different expression genes, enrichment and protein-protein interaction (PPI) enrichment analysis were used to detect the related pathways. RESULTS: Three gene modules (black, blue and turquoise) were significantly associated with MECT, enrichment analysis found that the long-term potentiation pathway was associated with MECT. PPI enrichment p-value of black, blue, turquoise module are 0.00127, <1×10-16 and 1.09×10-13, respectively. At the same time, EP300 is a key node in the PPI for genes in black module, which got from the transcriptome sequencing data. CONCLUSION: It is suggested that the long-term potentiation pathways were associated with biological mechanism of MECT.