Project description:In order to elucidate mechanisms underlying adverse effects of antipsychotic use in dementia we generated gene expression signatures for three antipsychotics representing a range of mechanisms of action relevant to the current landscape of drug development and clinical use in dementia: amisulpride (primarily a D2/D3 antagonist), risperidone (primarily a 5HT2A/D2 antagonist) and volinanserin (highly selective 5HT2A inverse agonist). We reported that the antipsychotic signatures would be score positively with conditions and diseases related to known side effects of their use in dementia such as cardiovascular and infectious diseases.
Project description:This SuperSeries is composed of the following subset Series: GSE38481: A gene co-expression network in whole blood of schizophrenia patients is independent of antipsychotic-use and enriched for brain-expressed genes [HumanRef-8 v3.0] GSE38484: A gene co-expression network in whole blood of schizophrenia patients is independent of antipsychotic-use and enriched for brain-expressed genes [HumanHT-12 V3.0] Refer to individual Series
Project description:Antipsychotic drugs are commonly used to treat psychosis, mood disorders, and anxiety. While there is indirect evidence that some component of the antipsychotic effect of these drugs may involve modulation of dopamine transmission, their mechanism of action is poorly understood. We hypothesized that antipsychotic drugs mediate their effects via epigenetic modulation. Here we tested the effect of an antipsychotic, olanzapine, on the methylation status of genes following chronic treatment. These effects have been revealed through significantly increased (p<0.01) DNA methylation of genes involved in dopaminergic and non-dopaminergic pathways including the glutamatergic, GABAergic, cholinergic, neuregulin and ErbB signaling pathways. The affected genes included GLS in hippocampus, NR1 in cerebellum and GLUD1 and NR2B in liver. Further, from a set of genes in the 22q11.2 micro-deletions that has been previously implicated in psychosis, 22 genes showed increased methylation following olanzapine treatment. Ingenuity Pathway Analysis (IPA) revealed that chronic olanzapine treatment significantly affected several important pathways such as CREB and CDK5 signaling (p=1.4E-05). Also, DNA replication, recombination and repair, cellular movement and cell cycle have been identified as the top networks affected by olanzapine. The results suggest that these downstream effects, aside from D2 blockade, may play a critical role in the biological actions of antipsychotics. These include altered expressions of relevant genes involved in GABAergic, glutamatergic, cholinergic, neuregulin and ErbB signaling pathways. Epigenetic mechanisms involving changes in DNA methylation could, therefore, explain the delay and individualized non-specificity of biological effects of olanzapine. The results also suggest that DNA methylation may play a role in the process of therapeutic efficacy of olanzapine by altering the transcriptome via tissue-specific methylation of genes involved in schizophrenia signaling pathways. comparison of olanzapine treated rats vs. control rats for genome-wide DNA methylation changes
Project description:Background. Schizophrenia is an idiopathic psychiatric disorder with a high degree of polygenicity. Evidence from genetics, single-cell, and pharmacological studies suggest an important overlap between genes involved in the etiology of schizophrenia and the cellular mechanisms of action of antipsychotics in medium spiny neurons (MSNs). Methods. We applied single-cell RNA-sequencing to striatal samples from C57BL/6J mice chronically exposed to a typical antipsychotic (haloperidol), an atypical antipsychotic (olanzapine), or placebo. We implemented careful statistical analyses to identify differentially expressed genes in two cell populations identified from the single-cell RNA-sequencing (MSNs and microglia) and applied multiple analysis pipelines to contextualize these findings. Results. Differential expression analysis showed that there was a larger share of differentially expressed genes (DEGs) in MSNs from mice treated with olanzapine vs. haloperidol. DEGs were enriched in broad loci implicated by genetic studies of schizophrenia, and we highlighted nine genes with convergent evidence. Pathway analyses highlighted alternative splicing, mitochondrial function, and neuron and synapse development as particularly engaged by antipsychotics. In microglia, we identified pathways involved in microglial activation and inflammation as part of the antipsychotic response. Conclusions. Our goal was to evaluate connections between schizophrenia genetic findings and cellular gene expression changes following antipsychotic exposure. We found that differential gene expression in MSNs from mice chronically treated with olanzapine converges on similar pathways and gene sets.
Project description:Antipsychotic drugs are commonly used to treat psychosis, mood disorders, and anxiety. While there is indirect evidence that some component of the antipsychotic effect of these drugs may involve modulation of dopamine transmission, their mechanism of action is poorly understood. We hypothesized that antipsychotic drugs mediate their effects via epigenetic modulation. Here we tested the effect of an antipsychotic, olanzapine, on the methylation status of genes following chronic treatment. These effects have been revealed through significantly increased (p<0.01) DNA methylation of genes involved in dopaminergic and non-dopaminergic pathways including the glutamatergic, GABAergic, cholinergic, neuregulin and ErbB signaling pathways. The affected genes included GLS in hippocampus, NR1 in cerebellum and GLUD1 and NR2B in liver. Further, from a set of genes in the 22q11.2 micro-deletions that has been previously implicated in psychosis, 22 genes showed increased methylation following olanzapine treatment. Ingenuity Pathway Analysis (IPA) revealed that chronic olanzapine treatment significantly affected several important pathways such as CREB and CDK5 signaling (p=1.4E-05). Also, DNA replication, recombination and repair, cellular movement and cell cycle have been identified as the top networks affected by olanzapine. The results suggest that these downstream effects, aside from D2 blockade, may play a critical role in the biological actions of antipsychotics. These include altered expressions of relevant genes involved in GABAergic, glutamatergic, cholinergic, neuregulin and ErbB signaling pathways. Epigenetic mechanisms involving changes in DNA methylation could, therefore, explain the delay and individualized non-specificity of biological effects of olanzapine. The results also suggest that DNA methylation may play a role in the process of therapeutic efficacy of olanzapine by altering the transcriptome via tissue-specific methylation of genes involved in schizophrenia signaling pathways.
Project description:Trifluoperazine (TFP), a typical antipsychotic primarily used for treating schizophrenia, exhibits anticancer effect on several types of cancer in recent years. Nevertheless, the effect of TFP on na-sopharyngeal carcinoma (NPC) is still unknown. In this study, we aimed to evaluate if TFP can be the potential therapeutic agent against NPC and to identify its underlying molecular mechanisms. We used four NPC cell lines, namely TW01, TW03, TW04, and BM, to assess the anticancer effects of TFP using cytotoxicity, wound healing, colony formation, and cell invasion assays. RNA se-quencing combined with Ingenuity Pathways Analysis was performed to identify the mechanism by which TFP influences NPC cells. Our data revealed that TFP decreased NPC cell viability in a dose-dependent manner. The invasion and migration of NPC cells were inhibited by TFP. RNA sequencing showed several anticancer molecular mechanisms after TFP administration. It is promising that the antipsychotic drug TFP can be used as a potential therapeutic regimen in NPC treatment in the future.
Project description:Antipsychotic drugs are classified as typical and atypical based on extrapyramidal effects. However, since the frontal cortex is one of the most important regions for antipsychotic actions, this study attempted to classify antipsychotic drugs based on gene expression in the frontal cortex. Chlorpromazine and thioridazine were selected as typical antipsychotics, and olanzapine and quetiapine as atypical antipsychotics. Since these drugs have similar chemical structures, the effect of the basic structure on gene expression can be eliminated. Cluster analysis of microarray experiments showed thioridazine and olanzapine constituted a robust cluster. K-means clustering separated 4-drug-administered mice into chlorpromazine-quetiapine and thioridazine-olanzapine groups. This classification scheme is different from that which is based on criteria currently used to group the typical and atypical drugs and suggests that antipsychotic drugs can be further separated into multiple groups. Keywords: repeat sample
Project description:Alzheimer’s disease (AD) is the most common subtype of dementia, followed by Vascular Dementia (VaD), and Dementia with Lewy Bodies (DLB). Recently, microRNAs (miRNAs) have received a lot of attention as the novel biomarkers for dementia. Here, using serum miRNA expression of 1,601 Japanese individuals, we investigated potential miRNA bio- markers and constructed risk prediction models, based on a supervised principal component analysis (PCA) logistic regression method, according to the subtype of dementia. The final risk prediction model achieved a high accuracy of 0.873 on a validation cohort in AD, when using 78 miRNAs: Accuracy = 0.836 with 86 miRNAs in VaD; Accuracy = 0.825 with 110 miRNAs in DLB. To our knowledge, this is the first report applying miRNA-based risk pre- diction models to a dementia prospective cohort. Our study demonstrates our models to be effective in prospective disease risk prediction; and with further improvement may contribute to practical clinical use in dementia.
Project description:We examined the effects of antipsychotic medications on the cell-specific epigenomics and transcriptomics in the frontal cortex of schizophrenic subjects.