Multi-omics analysis of paracetamol exposure identifies dysregulated genes involved in neurotoxicity and neuronal differentiation of human embryonic stem cells
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE220027 | GEO | 2023/08/31
REPOSITORIES: GEO
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Project description:Multi-omics analysis of paracetamol exposure identifies dysregulated genes involved in neurotoxicity and neuronal differentiation of human embryonic stem cells
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Project description:Selective serotonin reuptake inhibitors (SSRIs), including citalopram, are widely used antidepressants during pregnancy. However, the effects of prenatal exposure to citalopram on neurodevelopment remain poorly understood. We aimed to investigate the impact of citalopram exposure on early neuronal differentiation of human embryonic stem cells using a multi-omics approach. Citalopram induced time- and dose-dependent effects on gene expression and DNA methylation of genes involved in neurodevelopmental processes or linked to depression, such as BDNF, GDF11, CCL2, STC1, DDIT4 and GAD2. Single-cell RNA-sequencing analysis revealed distinct clusters of stem cells, neuronal progenitors and neuroblasts, where exposure to citalopram subtly influenced progenitor subtypes. Pseudotemporal analysis showed enhanced neuronal differentiation. Our findings suggest that citalopram exposure during early neuronal differentiation influences gene expression patterns associated with neurodevelopment and depression, providing insights into its potential neurodevelopmental impact and highlighting the importance of further research to understand the long-term consequences of prenatal SSRI exposure.
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Project description:Gliomas have highly variable clinical outcomes that are not adequately predicted on the basis of histologic class nor genetic markers. We performed a comprehensive analysis that integrated multi-omics datasets to elucidate factors influencing glioma prognosis. We detected 17 grade-related genes different in expression between LGG and GBM cohorts. By combining multi-layer information including genetic markers, DNA methylation and gene expression, we constructed two gene networks of relations from the grade-related genes. From the networks, we identified 178 prognostic genes whose activity states, in terms of DNA methylation and gene expression level, are relevant to prognostic outcomes of gliomas, with low activity associated with better outcomes. The efficacy of these 178 genes' activity states as prognostic factors beyond genetic markers, i.e. IDH1 or PTEN gene mutations, was validated externally. Among the 178 prognostic genes, we validated roles in gliomas for 121 genes from previous literature, and more importantly, we identified 67 novel candidate genes for glioma research. Expression of these 178 genes was particularly pronounced during fetal development in various brain regions. Our findings provide clues for understanding glioma prognosis and highlight some novel glioma-associated genes that warrant further investigation.
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Project description:BackgroundDespite significant therapeutic advances in improving lives of multiple myeloma (MM) patients, it remains mostly incurable, with patients ultimately becoming refractory to therapies. MM is a genetically heterogeneous disease and therapeutic resistance is driven by a complex interplay of disease pathobiology and mechanisms of drug resistance. We applied a multi-omics strategy using tumor-derived gene expression, single nucleotide variant, copy number variant, and structural variant profiles to investigate molecular subgroups in 514 newly diagnosed MM (NDMM) samples and identified 12 molecularly defined MM subgroups (MDMS1-12) with distinct genomic and transcriptomic features.ResultsOur integrative approach let us identify NDMM subgroups with transversal profiles to previously described ones, based on single data types, which shows the impact of this approach for disease stratification. One key novel subgroup is our MDMS8, associated with poor clinical outcome [median overall survival, 38 months (global log-rank p-value < 1 × 10-6)], which uniquely presents a broad genomic loss (> 9% of entire genome, t-test p value < 1e-5) driving dysregulation of various transcriptional programs affecting DNA repair and cell cycle/mitotic processes. This subgroup was validated on multiple independent datasets, and a master regulator analyses identified transcription factors controlling MDMS8 transcriptomic profile, including CKS1B and PRKDC among others, which are regulators of the DNA repair and cell cycle pathways.ConclusionUsing multi-omics unsupervised clustering we were able to discover a new high-risk multiple myeloma patient segment. This high-risk group presents diverse previously known genetic markers, but also a new characteristic defined by accumulation of genomic loss which seems to drive transcriptional dysregulation of cell cycle, DNA repair and DNA damage. Finally, our work identified various master regulators, including E2F2 and CKS1B as the genes controlling these key biological pathways.
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Project description:BackgroundPhosphorylation of proteins is a key step in the regulation of many cellular processes including activation of enzymes and signaling cascades. The abundance of a phosphorylated peptide (phosphopeptide) is determined by the abundance of its parent protein and the proportion of target sites that are phosphorylated.ResultsWe quantified phosphopeptides, proteins, and transcripts in heart, liver, and kidney tissue samples of mice from 58 strains of the Collaborative Cross strain panel. We mapped ~700 phosphorylation quantitative trait loci (phQTL) across the three tissues and applied genetic mediation analysis to identify causal drivers of phosphorylation. We identified kinases, phosphatases, cytokines, and other factors, including both known and potentially novel interactions between target proteins and genes that regulate site-specific phosphorylation. Our analysis highlights multiple targets of pyruvate dehydrogenase kinase 1 (PDK1), a regulator of mitochondrial function that shows reduced activity in the NZO/HILtJ mouse, a polygenic model of obesity and type 2 diabetes.ConclusionsTogether, this integrative multi-omics analysis in genetically diverse CC strains provides a powerful tool to identify regulators of protein phosphorylation. The data generated in this study provides a resource for further exploration.
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Project description:The use of fentanyl during pregnancy, whether by prescription or illicit use, may result in high blood levels that pose an early risk to fetal development. However, little is known regarding the neurotoxicity that might arise from excessive fentanyl exposure in growing organisms, particularly drug-related withdrawal symptoms. In this study, zebrafish embryos were exposed to fentanyl solutions (0.1, 1, and 5 mg/L) for 5 days post fertilization (dpf), followed by a 5-day recovery period, and then the larvae were evaluated for photomotor response, anxiety behavior, shoaling behavior, aggression, social preference, and sensitization behavior. Fentanyl solutions at 1 and 5 mg/L induced elevated anxiety, decreased social preference and aggressiveness, and behavioral sensitization in zebrafish larvae. The expression of genes revealed that embryonic exposure to fentanyl caused substantial alterations in neural activity (bdnf, c-fos) and neuronal development and plasticity (npas4a, egr1, btg2, ier2a, vgf). These results suggest that fentanyl exposure during embryonic development is neurotoxic, highlighting the importance of zebrafish as an aquatic species in research on the neurobehavioral effects of opioids in vertebrates.
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Project description:BackgroundAlterations of epigenetic modification patterns are potential markers of cancer. The current study characterized six histone modifications in osteosarcoma and identified epigenetically dysregulated long non-coding RNAs (epi-lncRNAs).MethodsMulti-omics data were obtained from osteosarcoma cell line SJSA1 and a normal cell line. Differentially expressed lncRNAs (DElncRNAs) between osteosarcoma and normal skeletal muscle were analyzed using Limma. MACS2 was applied to identify the "peaks" modified by each histone in the cell. Promoters or enhancers of DElncRNA were overlapped with differential histone-modified regions (DHMR) to screen epi-lncRNAs. Univariate and multivariate Cox regression analysis were performed to detect the genes closely related to the prognosis of osteosarcoma and to construct risk models.ResultsA total of 17 symbolic epi-lncRNA in osteosarcoma were screened, and 13 of them were differentially expressed between osteosarcoma and normal samples. Eight epi-lncRNAs were retained by Univariate Cox regression analysis. Four of these epi-lncRNAs were used to construct an epi-lncRNA signature. The risk score of each osteosarcoma sample in the high- or low-risk group was estimated according to the epi-lncRNA signature. The overall survival (OS) of the low-risk group was significantly better than that of the high-risk group. The area under the receiver operating characteristic (ROC) curve of the model was 0.79 and 0.82 for 1-, 3-, and 5-year OS, respectively.ConclusionOur results revealed the histone modification pattern in osteosarcoma and developed 4-epi-lncRNA signature to predict the prognosis of osteosarcoma, laying a foundation for the identification of highly specific epigenetic biomarkers for osteosarcoma.
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