Effects of antipsychotics risperidone and olanzapine on the striatum, liver, pancreas and adipose tissue
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PROVIDER: PRJNA748379 | ENA |
REPOSITORIES: ENA
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Project description:Analysis of gene expression in the striatum, the liver, the pancreas, and the visceral adipose tissue of mice treated for 28 days with a daily dose of an atypical antipsychotic: risperidone (1 mg/kg) or olanzapine (3.5 mg/kg). Results provide new insights into the molecular mechanisms underlying antipschotic effects, particularly in tissues relevant for antipsychotic-induced metabolic dysregulation. Antipsychotics are associated with weight gain and other metabolic abnormalities such as hyperglycemia, dyslipidemia and metabolic syndrome. We used microarrays to uncover the underlying molecular mechanisms and identify the key genes involved in AP-induced metabolic effects.
2021-09-08 | GSE180473 | GEO
Project description:This work reveals the effect of antipsychotics on DNA methylation using the cell model. After the treatment of antipsychotics, haloperidol and risperidone, DNA methylation profiles obtained by Illumina HumanMethylation450 beadchip were examined.
2021-11-02 | GSE185973 | GEO
Project description:Antipsychotics are usually the first option to treat schizophrenia; however, for a considerable fraction of patients, it lacks efficacy. Furthermore, there are no known biomarkers to indicate a treatment’s efficacy in a patient. Schizophrenia causes a large socioeconomic burden on countries along with an unquestionable impairment of the quality of life of patients and their relatives. As proteomics can identify, quantify, and characterize proteins in different conditions, it is a powerful tool to study complex diseases such as schizophrenia, also capable of revealing potential biomarkers. To improve treatment efficacy during the early stages of schizophrenia, a critical time period, molecular markers for a positive treatment response were sought. Blood plasma samples were collected in vivo from 26 patients before treatment with the atypical antipsychotics olanzapine and risperidone; they were then classified as good (GR) and poor (PR) responders. We were able to identify a potential panel of proteins that may predict a positive outcome to olanzapine and risperidone treatment. Although still exploratory, this data will assist in the development of personalized medicine strategies with potential clinical implementation
2020-06-01 | PXD015213 | Pride
Project description:Antipsychotics are the main line of treatment for schizophrenia, despite being effective only in about 50% of patients. Additionally, serious side effects may cause medication drop-out, aggravated by a lack of understanding about how these drugs act at molecular level. As proteomics is a suitable tool for studying multifactorial disorders, the main goal was to unravel signaling pathways in blood plasma associated with a positive treatment outcome for the atypical antipsychotics olanzapine and risperidone. Blood plasma was collected from schizophrenia patients six weeks after treatment (T6), and patients were classified as good or poor responders to olanzapine or risperidone, and then samples were compared to each patient's baseline (T0). All samples were analyzed using label-free quantitative shotgun proteomics. Samples were depleted of the 14 most abundant proteins in plasma, were digested, and then submitted to M-Class two-dimensional nano-liquid chromatography, coupled online to a Synapt G2-Si mass spectrometer. Data was obtained in MSE mode (data- independent acquisition) in combination with ion-mobility (HDMSE). The proteins found to be differentially abundant in good responders compared to poor responders for risperidone and olanzapine were functionally analyzed in silico using Ingenuity® Pathway Analysis and were found to be mostly involved with immune system functions. This data can contribute to better understand the biochemical signaling peripherally triggered by antipsychotic medication, and can eventually be used to help improve treatment outcome by predicting patient response as well as through the development of new medication or a combination of drugs that act on the immune system to reduce the duration of poor response periods in patients suffering with schizophrenia.
2020-06-01 | PXD015049 | Pride
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.
2021-04-14 | GSE171977 | GEO
Project description:SD rats were dosed with gold standard antipsychotic therapies, haloperidol or risperidone, at doses aimed at achieving therapeutically relevant drug exposures. Tissues were collected after 21 days of delivery to examine the impact of this treatment on gene expression in frontal cortex, hippocampus and striatum.
2015-03-16 | GSE66275 | GEO
Project description:We performed a pharmacotranscriptomic analysis of a human neuroblastoma cell line (SK-N-SH) exposed to risperidone to identify molecular mechanisms involved in the cellular response to risperidone and thus identify candidate genes for pharmacogenetic studies. This study is a part of a convergent functional genomic approach that plans to integrate the data presented here with: data from gene expression analysis of experimental animal brain under treatment with risperidone; and data from gene expression analysis of peripheral blood from first psychotic patients treated with risperidone. Gene expression was assessed by microarray (Human Genome U219 Array) in cells treated with risperidone 10 µM at 6, 24 and 48 h
2012-03-22 | E-GEOD-36678 | biostudies-arrayexpress
Project description:We performed a pharmacotranscriptomic analysis of a human neuroblastoma cell line (SK-N-SH) exposed to risperidone to identify molecular mechanisms involved in the cellular response to risperidone and thus identify candidate genes for pharmacogenetic studies. This study is a part of a convergent functional genomic approach that plans to integrate the data presented here with: data from gene expression analysis of experimental animal brain under treatment with risperidone; and data from gene expression analysis of peripheral blood from first psychotic patients treated with risperidone.
2012-03-22 | GSE36678 | GEO
Project description:To identify the molecular mechanisms that may initiate therapeutic effects, whole-genome expression profiling (Illumina Mouse WG-6 microarrays) of drug-induced alterations in the mouse brain was undertaken, with a focus on the time-course (1, 2, 4 and 8h) of gene expression changes produced by eighteen major psychotropic drugs: antidepressants, antipsychotics, anxiolytics, psychostimulants and opioids. The resulting database is freely accessible at www.genes2mind.org. Bioinformatics approaches led to the identification of three main drug-responsive genomic networks and indicated neurobiological pathways that mediate the alterations in transcription. Each tested psychotropic drug was characterized by a unique gene network expression profile related to its neuropharmacological properties. Functional links that connect expression of the networks to the development of neuronal adaptations (MAPK signaling pathway), control of brain metabolism (adipocytokine pathway), and organization of cell projections (mTOR pathway) were found. The additional data-sets are available at GEOX1 and GEOX2. The microarray experiment was performed to analyze time-course of drug-induced transcriptional response in C57BL/6J mouse striatum. Three antidepressants (bupropion 20 mg/kg, tranylcypromine 20 mg/kg, mianserin 20 mg/kg, i.p.), three anxiolytics (diazepam 5 mg/kg, buspirone 10 mg/kg, hydroxyzine 10 mg/kg, i.p.), and three antipsychotics (clozapine 3 mg/kg, risperidone 0.5 mg/kg, haloperidol 1 mg/kg) were selected for the comparison. Drug doses were previously reported as effective in mice and further tested in our laboratory. To analyze dynamics of early, intermediate and relatively late changes of mRNA abundance the experiment was performed in four time points (1, 2, 4 and 8h after drug administration). To exclude influence of drug injection and circadian rhythm on gene expression profile, control groups of saline or tween (1% Tween 80) treated and naïve animals were prepared for each time point. Design of the experiment assumed pooling of two animals per each array and using of three independent arrays per group. To provide appropriate balance in the whole dataset groups were equally divided between the array hybridization batches.
2013-07-18 | E-GEOD-48954 | biostudies-arrayexpress
Project description:Risperidone is an atypical antipsychotic that can cause substantial weight gain. The pharmacological targets and molecular mechanisms related to risperidone-induced lipogenesis (RIL) remain to be elucidated. Therefore, network pharmacology and further experimental validation were undertaken to explore the action mechanisms of RIL. In this study, RIL was systematically analyzed using integrating multiple databases through integrated network pharmacology, transcriptomics, molecular docking, and molecular experiment analysis. The potential signaling pathways for RIL were identified and experimentally validated using Gene Ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Our experimental data showed that Risperidone promotes adipocyte differentiate and lipid accumulation. And network pharmacology and GO analyses showed that risperidone induced adipocyte metabolism, differentiation, and lipid accumulation related functions. Intersecting analysis, molecular docking, and pathway validation analysis indicated that risperidone activated adipocytokine signaling pathway related genes by targeting MAPK14 (Mitogen-activated protein kinase 14), MAPK8 (Mitogen-activated protein kinase 8), and RXRA (Retinoic acid receptor RXR-alpha), thereby inhibiting long-chain fatty acid beta-oxidation by suppressing STAT3 (Signal transducer and activator of transcription 3) expression and phosphorylation. This study suggested that Risperidone increases adipocyte lipid accumulation by plausible inhibiting long-chain fatty acid beta-oxidation through targeting MAPK14, MAPK8, and RXRA.
2022-05-11 | GSE198053 | GEO