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Functional modular networks identify the pivotal genes associated with morphine addiction and potential drug therapies
BACKGROUND: Chronic morphine usage induces lasting molecular and microcellular adaptations in distinct brain areas, resulting in addiction-related behavioural abnormalities, drug-seeking, and relapse. Nonetheless, the mechanisms of action of the genes responsible for morphine addiction have not been...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10155436/ https://www.ncbi.nlm.nih.gov/pubmed/37138216 http://dx.doi.org/10.1186/s12871-023-02111-2 |
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author | Jiang, Yage Wei, Donglei Xie, Yubo |
author_facet | Jiang, Yage Wei, Donglei Xie, Yubo |
author_sort | Jiang, Yage |
collection | PubMed |
description | BACKGROUND: Chronic morphine usage induces lasting molecular and microcellular adaptations in distinct brain areas, resulting in addiction-related behavioural abnormalities, drug-seeking, and relapse. Nonetheless, the mechanisms of action of the genes responsible for morphine addiction have not been exhaustively studied. METHODS: We obtained morphine addiction-related datasets from the Gene Expression Omnibus (GEO) database and screened for Differentially Expressed Genes (DEGs). Weighted Gene Co-expression Network Analysis (WGCNA) functional modularity constructs were analyzed for genes associated with clinical traits. Venn diagrams were filtered for intersecting common DEGs (CDEGs). Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for functional annotation. Protein–protein interaction network (PPI) and CytoHubba were used to screen for hub genes. Potential treatments for morphine addiction were figured out with the help of an online database. RESULTS: Sixty-five common differential genes linked to morphine addiction were identified, and functional enrichment analysis showed that they were primarily involved in ion channel activity, protein transport, the oxytocin signalling pathway, neuroactive ligand-receptor interactions, and other signalling pathways. Based on the PPI network, ten hub genes (CHN2, OLIG2, UGT8A, CACNB2, TIMP3, FKBP5, ZBTB16, TSC22D3, ISL1, and SLC2A1) were checked. In the data set GSE7762, all of the Area Under Curve (AUC) values for the hub gene Receiver Operating Characteristic (ROC) curves were greater than 0.8. We also used the DGIdb database to look for eight small-molecule drugs that might be useful for treating morphine addiction. CONCLUSIONS: The hub genes are crucial genes associated with morphine addiction in the mouse striatum. The oxytocin signalling pathway may play a vital role in developing morphine addiction. |
format | Online Article Text |
id | pubmed-10155436 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-101554362023-05-04 Functional modular networks identify the pivotal genes associated with morphine addiction and potential drug therapies Jiang, Yage Wei, Donglei Xie, Yubo BMC Anesthesiol Research BACKGROUND: Chronic morphine usage induces lasting molecular and microcellular adaptations in distinct brain areas, resulting in addiction-related behavioural abnormalities, drug-seeking, and relapse. Nonetheless, the mechanisms of action of the genes responsible for morphine addiction have not been exhaustively studied. METHODS: We obtained morphine addiction-related datasets from the Gene Expression Omnibus (GEO) database and screened for Differentially Expressed Genes (DEGs). Weighted Gene Co-expression Network Analysis (WGCNA) functional modularity constructs were analyzed for genes associated with clinical traits. Venn diagrams were filtered for intersecting common DEGs (CDEGs). Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for functional annotation. Protein–protein interaction network (PPI) and CytoHubba were used to screen for hub genes. Potential treatments for morphine addiction were figured out with the help of an online database. RESULTS: Sixty-five common differential genes linked to morphine addiction were identified, and functional enrichment analysis showed that they were primarily involved in ion channel activity, protein transport, the oxytocin signalling pathway, neuroactive ligand-receptor interactions, and other signalling pathways. Based on the PPI network, ten hub genes (CHN2, OLIG2, UGT8A, CACNB2, TIMP3, FKBP5, ZBTB16, TSC22D3, ISL1, and SLC2A1) were checked. In the data set GSE7762, all of the Area Under Curve (AUC) values for the hub gene Receiver Operating Characteristic (ROC) curves were greater than 0.8. We also used the DGIdb database to look for eight small-molecule drugs that might be useful for treating morphine addiction. CONCLUSIONS: The hub genes are crucial genes associated with morphine addiction in the mouse striatum. The oxytocin signalling pathway may play a vital role in developing morphine addiction. BioMed Central 2023-05-03 /pmc/articles/PMC10155436/ /pubmed/37138216 http://dx.doi.org/10.1186/s12871-023-02111-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Jiang, Yage Wei, Donglei Xie, Yubo Functional modular networks identify the pivotal genes associated with morphine addiction and potential drug therapies |
title | Functional modular networks identify the pivotal genes associated with morphine addiction and potential drug therapies |
title_full | Functional modular networks identify the pivotal genes associated with morphine addiction and potential drug therapies |
title_fullStr | Functional modular networks identify the pivotal genes associated with morphine addiction and potential drug therapies |
title_full_unstemmed | Functional modular networks identify the pivotal genes associated with morphine addiction and potential drug therapies |
title_short | Functional modular networks identify the pivotal genes associated with morphine addiction and potential drug therapies |
title_sort | functional modular networks identify the pivotal genes associated with morphine addiction and potential drug therapies |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10155436/ https://www.ncbi.nlm.nih.gov/pubmed/37138216 http://dx.doi.org/10.1186/s12871-023-02111-2 |
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