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THC exposure of human iPSC neurons impacts genes associated with neuropsychiatric disorders.

Boris Guennewig | Maina Bitar | Ifeanyi Obiorah | James Hanks | Elizabeth A O'Brien | Dominik C Kaczorowski | Yasmin L Hurd | Panos Roussos | Kristen J Brennand | Guy Barry
Translational psychiatry | 2018

There is a strong association between cannabis use and schizophrenia but the underlying cellular links are poorly understood. Neurons derived from human-induced pluripotent stem cells (hiPSCs) offer a platform for investigating both baseline and dynamic changes in human neural cells. Here, we exposed neurons derived from hiPSCs to Δ9-tetrahydrocannabinol (THC), and identified diagnosis-specific differences not detectable in vehicle-controls. RNA transcriptomic analyses revealed that THC administration, either by acute or chronic exposure, dampened the neuronal transcriptional response following potassium chloride (KCl)-induced neuronal depolarization. THC-treated neurons displayed significant synaptic, mitochondrial, and glutamate signaling alterations that may underlie their failure to activate appropriately; this blunted response resembles effects previously observed in schizophrenia hiPSC- derived neurons. Furthermore, we show a significant alteration in THC-related genes associated with autism and intellectual disability, suggesting shared molecular pathways perturbed in neuropsychiatric disorders that are exacerbated by THC.

Pubmed ID: 29691375

Associated grants

  • Agency: NIDA NIH HHS, United States
    Id: R01 DA030359
  • Agency: NIMH NIH HHS, United States
    Id: R01 MH101454
  • Agency: NIA NIH HHS, United States
    Id: R01 AG050986
  • Agency: NIMH NIH HHS, United States
    Id: R01 MH109677

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This is a list of tools and resources that we have found mentioned in this publication.


ATCC (tool)

RRID:SCR_001672

Global nonprofit biological resource center (BRC) and research organization that provides biological products, technical services and educational programs to private industry, government and academic organizations. Its mission is to acquire, authenticate, preserve, develop and distribute biological materials, information, technology, intellectual property and standards for the advancement and application of scientific knowledge. The primary purpose of ATCC is to use its resources and experience as a BRC to become the world leader in standard biological reference materials management, intellectual property resource management and translational research as applied to biomaterial development, standardization and certification. ATCC characterizes cell lines, bacteria, viruses, fungi and protozoa, as well as develops and evaluates assays and techniques for validating research resources and preserving and distributing biological materials to the public and private sector research communities.

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BiNGO: A Biological Networks Gene Ontology tool (tool)

RRID:SCR_005736

The Biological Networks Gene Ontology tool (BiNGO) is an open-source Java tool to determine which Gene Ontology (GO) terms are significantly overrepresented in a set of genes. BiNGO can be used either on a list of genes, pasted as text, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy, and takes advantage of Cytoscape''''s versatile visualization environment to produce an intuitive and customizable visual representation of the results. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

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FISHER (tool)

RRID:SCR_009181

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 1st, 2022. Software application for genetic analysis of classical biometric traits like blood pressure or height that are caused by a combination of polygenic inheritance and complex environmental forces. (entry from Genetic Analysis Software)

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Gene Ontology (tool)

RRID:SCR_002811

Computable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.

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HGNC (tool)

RRID:SCR_002827

Worldwide authority that approves standardized nomenclature to gene name and symbol, short form abbreviation, for each known human gene and stores all approved symbols in HGNC database. Approved human gene nomenclature. Database of gene symbols. Manually curated genes into family sets based on shared characteristics such as homology, function or phenotype. Data for protein-coding genes, pseudogenes, non-coding RNAs, phenotypes and genomic features.

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Cytoscape (tool)

RRID:SCR_003032

Software platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.

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Systems Transcriptional Activity Reconstruction (tool)

RRID:SCR_005622

A next-generation web-based application that aims to provide an integrated solution for both visualization and analysis of deep-sequencing data, along with simple access to public datasets.

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KEGG (tool)

RRID:SCR_012773

Integrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.

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edgeR (tool)

RRID:SCR_012802

Bioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.

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RSEM (tool)

RRID:SCR_013027

Software package for quantifying gene and isoform abundances from single end or paired end RNA Seq data. Accurate transcript quantification from RNA Seq data with or without reference genome. Used for accurate quantification of gene and isoform expression from RNA-Seq data.

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