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.

Correlation between duration of untreated psychosis and long-term prognosis in chronic schizophrenia.

Objective: To explore the relationship between the Duration of Untreated Psychosis (DUP) and long-term clinical outcome, cognitive and social function in patients with chronic schizophrenia (SCZ). Methods: A total of 248 subjects with chronic SCZ were enrolled in this study, including 156 in the short DUP group and 92 in the long DUP group. The Positive and Negative Symptoms Scale (PANSS), the Brief Negative Symptoms Scale (BNSS), the Global Assessment of Functioning (GAF) scale and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) were used to assess all of the subjects. Results: The negative symptom scores (the PANSS and BNSS) of subjects with long DUP were significantly higher than that in subjects with short DUP. The scores of visual span and speech function in the short DUP group were significantly higher, indicative of decreasing cognitive function with time. In terms of social function, the short DUP group scored higher, with a statistically significant difference. Meanwhile, we found that the length of DUP was positively correlated with the negative symptom score of the PANSS, negatively correlated with visual span scores, and GAF scores. Conclusion: This study demonstrated that the DUP remained a significant association with negative symptom and cognition in long period of chronic SCZ.

Persistent reshaping of cohesive sediment towards stable flocs by turbulence.

Cohesive sediment forms flocs of various sizes and structures in the natural turbulent environment. Understanding flocculation is critical in accurately predicting sediment transport and biogeochemical cycles. In addition to aggregation and breakup, turbulence also reshapes flocs toward more stable structures. An Eulerian-Lagrangian framework has been implemented to investigate the effect of turbulence on flocculation by capturing the time-evolution of individual flocs. We have identified two floc reshaping mechanisms, namely breakage-regrowth and restructuring by hydrodynamic drag. Surface erosion is found to be the primary breakup mechanism for strong flocs, while fragile flocs tend to split into fragments of similar sizes. Aggregation of flocs of sizes comparable to or greater than the Kolmogorov scale is modulated by turbulence with lower aggregation efficiency. Our findings highlight the limiting effects of turbulence on both floc size and structure.

Demographic characteristics, family environment and psychosocial factors affecting internet addiction in Chinese adolescents.

BACKGROUND: Internet addiction of adolescents has aroused social concern recently. The present study aims to identify predicting factors of internet addiction on adolescents. METHODS: The demographic characteristics and psychological characteristics of 50, 855 middle school students were investigated through Internet Gaming Disorder Scale- Short Form(IGDS9-SF), Smartphone Application-Based Addiction Scale (SABAS), Bergen Social Media Addiction Scale (BSMAS), Strengths and Difficulties Questionnaire-students (SDQS), 16-Item Version of the Prodromal Questionnaire (PQ-16), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7-item (GAD-7), Multidimensional Peer Victimization Scale (MPVS), Warwick-Edinburgh Mental Well-being Scale (WEMWBS), and Connor-Davidson Resilience Scale (CD-RISC10) were used to analyze factors associated with internet addiction by Pearson correlation coefficient and multiple hierarchical regression. RESULTS: IGDS9-SF, SABAS and BSMAS are positively correlated with SDQS, PQ-16, PHQ-9, GAD-7 and MPVS (r-values ranging from 0.180 to 0.488, p < 0.01). IGDS9-SF, SABAS and BSMAS are negatively correlated with WEMWB and CD-RISC (r-values ranging from -0.242 ~ -0.338, p < 0.01). Multiple hierarchical regression shown gender, one-child, twins, left-behind, rural, education (father), drink (father), smoke (father), CD-RISC-10, SDQS, PQ-16, PHQ-9, GAD-7 and MPVS predicted 32.7 % of the variance in internet gaming disorder (IGD) (F = 1174.949, p < 0.001). Group (junior and senior), Gender, Age, One-Child, Twins, Village, Education (father), Drink (father), Drink (mother), Smoke (father), WEMWBS, CD-RISC-10, SDQS, PQ-16, PHQ-9, GAD-7 and MPVS predicted 28.9 % of the total variance in social media addiction (SMA) (F = 982.932, p < 0.001). Fifteen variables [Gender, Age, Twins, Left-behind, Residence, Residence, Education (mother), Drink(father), Drink (mother), Smoke (father), WEMWBS, CD-RISC-10, PHQ-9, GAD-7 and MPVS] predicted 30.7 % of the variance in smartphone addiction (SA) (F = 1076.02, p < 0.001). CONCLUSION: The present study found that demographic characteristics, family environment and psychosocial factors were associated with internet gaming addiction, social media addiction and smartphone addiction. Negative psychological factors (such as anxiety and depression) play an important role in different behavioral addictions.

Altered spontaneous brain activity in major depressive disorder: An activation likelihood estimation meta-analysis.

BACKGROUND: Wide application of resting-state functional magnetic resonance imaging (fMRI) in psychiatric research has revealed that major depressive disorder (MDD) manifest abnormal neural activities in several brain regions involving key resting state networks. However, inconsistent results have hampered our understanding of the exact neuropathology associated with MDD. Therefore, our aim was to conduct a meta-analysis to identify the consistent vulnerable brain regions of MDD in resting state, and to reveal the potential pathogenesis of MDD. METHODS: A systematic review analysis was conducted on studies involving brain resting-state changes in MDD using low-frequency amplitude (ALFF), fractional low-frequency amplitude (fALFF) and regional homogeneity (ReHo) analysis. The meta-analysis was based on the activation likelihood estimation method, using the software of Ginger ALE 2.3. RESULTS: 25 studies (892 MDD and 799 healthy controls) were included. Based on the meta-analysis results of ReHo, we found robust reduction of resting-state spontaneous brain activity in MDD, including the left cuneus and right middle occipital gyrus (cluster size = 216, 256 mm3, uncorrected P < 0.0001), while no increased spontaneous activation in any of the brain regions. We also found reduced ALFF in the left middle occipital gyrus (cluster size = 224 mm3, uncorrected P < 0.0001), and no increased spontaneous brain activation in any regions. CONCLUSION: Our meta-analysis study using the activation likelihood estimation method demonstrated that MDD showed significant abnormalities in spontaneous neural activity, compared with healthy controls, mainly in areas associated with visual processing, such as the cuneus and the middle occipital gyrus. Dysfunction of these brain regions may be one of the pathogenesis of MDD.

Sleep duration and auditory hallucinations: Genetic correlation and two-sample Mendelian randomization study.

OBJECTIVES: Previous studies have found that sleep problems are associated with psychotic experiences (PEs) across clinical designs, but many confounding factors from uncertain variables have been unclear in observational designs. The aim of the present study was to detect the genetic correlations and causal relationship between sleep-related traits and PEs using the largest current genome-wide association study (GWAS) summary statistics. METHODS: GWAS results were obtained for positive PEs (N = 116,787-117,794) and sleep-related traits [insomnia complaints (N = 386,533), morningness (N = 345,552), sleep duration (N = 384,317), ease of getting up in the morning (N = 385,949), daytime napping (N = 386,577), daytime sleepiness (N = 386,548), and snoring (N = 359,916)]. Linkage disequilibrium score regression (LDSC) was used to investigate genetic correlations. Mendelian randomization (MR) was conducted on trait pairs with significant genetic associations. RESULTS: We found that auditory hallucinations were significantly genetically correlated with insomnia complaints (rg = -0.27, p = 1.1 × 10-3), sleep duration (rg = 0.21, p = 9.7 × 10-3), and ease of getting up (rg = 0.31, p = 2 × 10-4). Visual hallucinations and insomnia complaints were highly genetically correlated (rg = 0.36, p = 6.4 × 10-5). Mendelian randomization indicated a unidirectional causal relationship between sleep duration with auditory hallucinations (ß = -0.93, p = 7.9 × 10-4 for sleep duration as the exposure). We used large GWAS summary statistics across the LDSC and MR programs to determine that sleep duration as exposure to increase the risk of auditory hallucinations. CONCLUSIONS: Taken together, these findings suggest that treatment of sleep problems should be considered as a higher priority for future mental health services.

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.

A Combined Analysis of Genetically Correlated Traits Identifies Genes and Brain Regions for Insomnia.

AIMS: Previous studies have inferred that there is a strong genetic component in insomnia. However, the etiology of insomnia is still unclear. This study systematically analyzed multiple genome-wide association study (GWAS) data sets with core human pathways and functional networks to detect potential gene pathways and networks associated with insomnia. METHODS: We used a novel method, multitrait analysis of genome-wide association studies (MTAG), to combine 3 large GWASs of insomnia symptoms/complaints and sleep duration. The i-Gsea4GwasV2 and Reactome FI programs were used to analyze data from the result of MTAG analysis and the nominally significant pathways, respectively. RESULTS: Through analyzing data sets using the MTAG program, our sample size increased from 113,006 subjects to 163,188 subjects. A total of 17 of 1,816 Reactome pathways were identified and showed to be associated with insomnia. We further revealed 11 interconnected functional and topologically interacting clusters (Clusters 0 to 10) that were associated with insomnia. Based on the brain transcriptome data, it was found that the genes in Cluster 4 were enriched for the transcriptional coexpression profile in the prenatal dorsolateral prefrontal cortex (P = 7 × 10-5), inferolateral temporal cortex (P = 0.02), medial prefrontal cortex (P < 1 × 10-5), and amygdala (P < 1 × 10-5), and detected RPA2, ORC6, PIAS3, and PRIM2 as core nodes in these 4 brain regions. CONCLUSIONS: The findings provided new genes, pathways, and brain regions to understand the pathology of insomnia.

The role of genes affected by human evolution marker GNA13 in schizophrenia.

Numerous variants associated with increased risk for SCZ have undergone positive selection and were associated with human brain development, but which brain regions and developmental stages were influenced by the positive selection for SCZ risk alleles are unclear. We analyzed SCZ using summary statistics from a genome-wide association study (GWAS) from the Psychiatric Genomics Consortium (PGC). Machine-learning scores were used to investigate two natural-selection scenarios: complete selection (loci where a selected allele has reached fixation) and incomplete selection (loci where a selected allele has not yet reached fixation). Based on the p value of single nucleotide polymorphisms (SNPs) with selection scores in the top 5%, we formed five subgroups: p < 0.0001, 0.001, 0.01, 0.05, or 0.1. We found that 48 and 29 genes (p < 0.0001) in complete and incomplete selection, respectively, were enrichedfor the transcriptionalco-expressionprofilein theprenatal dorsolateral prefrontal cortex (DFC), inferior parietal cortex (IPC), and ventrolateral prefrontal cortex (VFC). Core genes (GNA13, TBC1D19, and ZMYM4) involved in regulating early brain development were identified in these three brain regions. RNA sequencing for primary cortical neurons that were transfected Gna13 overexpressed lentivirus demonstrated that 135 gene expression levels changed in the Gna13 overexpressed groups compared with the controls. Gene-set analysis identified important associations among common variants of these 13 genes, which were associated with neurodevelopment and putamen volume [p = 0.031; family-wise error correction (FWEC)], SCZ (p = 0.022; FWEC). The study indicate that certain SCZ risk alleles were likely to undergo positive selection during human evolution due to their involvement in the development of prenatal DFC, IPC and VFC, and suggest that SCZ is related to abnormal neurodevelopment.

Systematic genetic analyses of GWAS data reveal an association between the immune system and insomnia.

BACKGROUND: Previous studies have inferred a strong genetic component for insomnia. However, the etiology of insomnia is still unclear. The aim of the current study was to explore potential biological pathways, gene networks, and brain regions associated with insomnia. METHODS: Using pathways (gene sets) from Reactome, we carried out a two-stage gene set enrichment analysis strategy. From a large genome-wide association studies (GWASs) of insomnia symptoms (32,155 cases/26,973 controls), significant gene sets were tested for replication in other large GWASs of insomnia complaints (32,384 cases/80,622 controls). After the network analysis of unique genes within the replicated pathways, a gene set analysis for genes in each cluster/module of the enhancing neuroimaging genetics through meta-analysis GWAS data was performed for the volumes of the intracranial and seven subcortical regions. RESULTS: A total of 31 of 1,816 Reactome pathways were identified and showed associations with insomnia risk. In addition, seven functionally and topologically interconnected clusters (clusters 0-6) and six gene modules (named Yellow, Blue, Brown, Green, Red, and Turquoise) were associated with insomnia. Moreover, significant associations were detected between common variants of the genes in Cluster 2 with hippocampal volume (p = 0.035; family wise error [FWE] correction) and the red module with intracranial volume (p = 0.047; FWE correction). Functional enrichment for genes in the Cluster 2 and the Red module revealed the involvement of immune responses, nervous system development, NIK/NF-kappaB signaling, and I-kappaB kinase/NF-kappaB signaling. Core genes (UBC, UBB, and UBA52) in the interconnected functional network were found to be involved in regulating brain development. CONCLUSIONS: The current study demonstrates that the immune system and the hippocampus may play central roles in neurodevelopment and insomnia risk.

Evidence for an oncogenic role of HOXC6 in human non-small cell lung cancer.

BACKGROUND: Identification of specific biomarkers is important for the diagnosis and treatment of non-small cell lung cancer (NSCLC). HOXC6 is a homeodomain-containing transcription factor that is highly expressed in several human cancers; however, its role in NSCLC remains unknown. METHODS: The expression and protein levels of HOXC6 were assessed in NSCLC tissue samples by Quantitative real-time PCR (qRT-PCR) and immunohistochemistry, respectively. HOXC6 was transfected into the NSCLC cell lines A549 and PC9, and used to investigate its effect on proliferation, migration, and invasion using CFSE, wound healing, and Matrigel invasion assays. Next-generation sequencing was also used to identify downstream targets of HOXC6 and to gain insights into the molecular mechanisms underlying its biological function. RESULTS: HOXC6 expression was significantly increased in 66.6% (20/30) of NSCLC tumor samples in comparison to normal controls. HOXC6 promoted proliferation, migration, and invasion of NSCLC cells in vitro. RNA-seq analysis demonstrated the upregulation of 310 and 112 genes in A549-HOXC6 and PC9-HOXC6 cells, respectively, and the downregulation of 665 and 385 genes in A549-HOXC6 and PC9-HOXC6 cells, respectively. HOXC6 was also found to regulate the expression of genes such as CEACAM6, SPARC, WNT6, CST1, MMP2, and KRT13, which have documented pro-tumorigenic functions. DISCUSSION: HOXC6 is highly expressed in NSCLC, and it may enhance lung cancer progression by regulating the expression of pro-tumorigenic genes involved in proliferation, migration, and invasion. Our study highlighted the oncogenic potential of HOXC6, and suggests that it may be a novel biomarker for the diagnosis and treatment of NSCLC.

HOXC6 promotes migration, invasion and proliferation of esophageal squamous cell carcinoma cells via modulating expression of genes involved in malignant phenotypes.

BACKGROUND: HOXC6 is a member of the HOX gene family. The elevated expression of this gene occurs in prostate and breast cancers. However, the role of HOXC6 in esophageal squamous cell carcinoma (ESCC) remains largely uninvestigated. METHODS: The expression of HOXC6 was examined by immunohistochemistry, quantitative real-time PCR and immunoblotting assays. The lentivirus-mediated expression of HOXC6 was verified at mRNA and protein levels. Wound healing and Matrigel assays were performed to assess the effect of HOXC6 on the migration and invasion of cancer cells. The growth curving, CCK8, and colony formation assays were utilized to access the proliferation capacities. RNA-seq was performed to evaluate the downstream targets of HOXC6. Bioinformatic tool was used to analyze the gene expression. RESULTS: HOXC6 was highly expressed in ESCC tissues. HOXC6 overexpression promoted the migration, invasion, and proliferation of both Eca109 and TE10 cells. There were 2,155 up-regulated and 759 down-regulated genes in Eca109-HOXC6 cells and 95 up-regulated and 47 down-regulated genes in TE10-HOXC6 cells compared with the results of control. Interestingly, there were only 20 common genes, including 17 up-regulated and three down-regulated genes with similar changes upon HOXC6 transfection in both cell lines. HOXC6 activated several crucial genes implicated in the malignant phenotype of cancer cells. DISCUSSION: HOXC6 is highly expressed in ESCC and promotes malignant phenotype of ESCC cells. HOXC6 can be used as a new therapeutic target of ESCC.

Systematic genetic analyses of genome-wide association study data reveal an association between the key nucleosome remodeling and deacetylase complex and bipolar disorder development.

BACKGROUND: Genome-wide association studies (GWASs) are used to identify genetic variants for association with bipolar disorder (BD) risk; however, each GWAS can only reveal a small fraction of this association. This study systematically analyzed multiple GWAS data sets to provide further insights into potential causal BD processes by integrating the results of Psychiatric Genomics Consortium Phase I (PGC-I) for BD with core human pathways and functional networks. METHODS: The i-Gsea4GwasV2 program was used to analyze data from the PGC-I GWAS for BD (the pathways came from Reactome), as well as the nominally significant pathways. We established a gene network of the significant pathways and performed a gene set analysis for each gene cluster of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) GWAS data for the volumes of the intracranial region and seven subcortical regions. RESULTS: A total of 30 of 1816 Reactome pathways were identified and showed associations with BD risk. We further revealed 22 interconnected functional and topologically interacting clusters (Clusters 0-21) that were associated with BD risk. Moreover, we obtained brain transcriptome data from BrainSpan and found significant associations between common variants of the genes in Cluster 1 with the hippocampus (HIP; P = .026; family-wise error [FWE] correction) and amygdala (AMY; P = .016; FEW correction) in Cluster 8 with HIP (P = .022; FWE correction). The genes in Cluster 1 were enriched for the transcriptional co-expression profile in the prenatal AMY, and core genes (CDH4, MTA2, RBBP4, and HDAC2) were identified to be involved in regulating early brain development. CONCLUSION: This study demonstrated that the HIP and AMY play a central role in neurodevelopment and BD risk.

[Exploration of common biological pathways for attention deficit hyperactivity disorder and low birth weight].

OBJECTIVE: To explore common biological pathways for attention deficit hyperactivity disorder (ADHD) and low birth weight (LBW). METHODS: Thei-Gsea4GwasV2 software was used to analyze the result of genome-wide association analysis (GWAS) for LBW (pathways were derived from Reactome), and nominally significant (P< 0.05, FDR< 0.25) pathways were tested for replication in ADHD.Significant pathways were analyzed with DAPPLE and Reatome FI software to identify genes involved in such pathways, with each cluster enriched with the gene ontology (GO). The Centiscape2.0 software was used to calculate the degree of genetic networks and the betweenness value to explore the core node (gene). Weighed gene co-expression network analysis (WGCNA) was then used to explore the co-expression of genes in these pathways.With gene expression data derived from BrainSpan, GO enrichment was carried out for each gene module. RESULTS: Eleven significant biological pathways was identified in association with LBW, among which two (Selenoamino acid metabolism and Diseases associated with glycosaminoglycan metabolism) were replicated during subsequent ADHD analysis. Network analysis of 130 genes in these pathways revealed that some of the sub-networksare related with morphology of cerebellum, development of hippocampus, and plasticity of synaptic structure. Upon co-expression network analysis, 120 genes passed the quality control and were found to express in 3 gene modules. These modules are mainly related to the regulation of synaptic structure and activity regulation. CONCLUSION: ADHD and LBW share some biological regulation processes. Anomalies of such proces sesmay predispose to ADHD.

Purification of coumarin compounds from Cortex fraxinus by adsorption chromatography.

In this paper, a chromatographic method for isolation and purification of coumarin compounds from Cortex fraxinus was established by using Superose 12 as the separation media for the first time. The conditions for separation were optimized. Four kinds of coumarin compounds including aesuletin, aesculin, fraxetin and fraxin were obtained. The purity of these compounds were 98.5, 99.1, 97.9 and 97.3%, respectively, which were determined by HPLC area normalization method. The chemical structures of the separated compounds were identified according to (1)H and (13)C nuclear magnetic resonance data. The retention behavior of the separated coumarin compounds on Superose 12 was also discussed. The retention is based on a mixture of hydrogen bonding and hydrophobic interactions between the coumarin compounds and the residues of the cross-linking reagents used in the manufacturing process of Superose 12. The results of this paper indicate that Superose 12 is not only suitable for size-exclusion chromatography of proteins and other biological macromolecules but also for low-molecular-weight natural products.