Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 May 3;23(1):151.
doi: 10.1186/s12871-023-02111-2.

Functional modular networks identify the pivotal genes associated with morphine addiction and potential drug therapies

Yage Jiang #  1 , Donglei Wei #  2 , Yubo Xie  3   4
Affiliations

Functional modular networks identify the pivotal genes associated with morphine addiction and potential drug therapies

Yage Jiang et al. BMC Anesthesiol. .

Retraction in

Abstract

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.

Keywords: Biomarkers; Morphine addiction; Opioids; Oxytocin signalling pathway; Weighted gene co-expression network analysis.

PubMed Disclaimer

Conflict of interest statement

The database contains samples downloaded from the GEO database (https://www.ncbi.nlm.nih.gov/geo/) and has received ethical approval. Users can download relevant data for free and publish relevant articles for research purposes. Our research is based on data from public sources. Therefore there are no ethical or other conflicts of interest.

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Weighted gene co-expression network analysis (WGCNA) construction. A Identification of co-expression modules in morphine addiction. B Correlation of gene modules with morphine addiction
Fig. 2
Fig. 2
Venn diagram analysis of common differentially expressed genes (CDEGs) between DEGs and functional module genes
Fig. 3
Fig. 3
Functional annotation and pathway enrichment analysis of differentially expressed genes (DEGs). A Histogram of GO enrichment analysis. B Circle diagram of GO analysis. C KEGG pathway enrichment analysis bubble diagram. D Circle diagram of KEGG analysis
Fig. 4
Fig. 4
Functional annotation and pathway enrichment analysis of common DEGs (CDEGs). A Histogram of GO enrichment analysis. B Circle diagram of GO analysis. C KEGG pathway enrichment analysis bubble diagram. D Circle diagram of KEGG analysis
Fig. 5
Fig. 5
PPI protein interaction network of CDEGs and Hub genes
Fig. 6
Fig. 6
Heat map and box plot showing the expression of Hub genes
Fig. 7
Fig. 7
A-J Receiver operating characteristic (ROC) and area under the curve (AUC) of 10 Hub genes. K Column line graph of Hub genes. L Calibration plots of the column line graphs
Fig. 8
Fig. 8
Twenty potential microRNA regulators of Hub genes
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Lee S, Park Y, Han E, Choi H, Chung H, Oh SM, et al. Thebaine in hair as a marker for chronic use of illegal opium poppy substances. Forensic Sci Int. 2011;204(1–3):115–118. doi: 10.1016/j.forsciint.2010.05.013. - DOI - PubMed
    1. Blanco C, Volkow ND. Management of opioid use disorder in the USA: present status and future directions. Lancet. 2019;393(10182):1760–1772. doi: 10.1016/s0140-6736(18)33078-2. - DOI - PubMed
    1. Kim J, Ham S, Hong H, Moon C, Im HI. Brain reward circuits in morphine addiction. Mol Cells. 2016;39(9):645–653. doi: 10.14348/molcells.2016.0137. - DOI - PMC - PubMed
    1. Roy S, Guo X, Kelschenbach J, Liu Y, Loh HH. In vivo activation of a mutant mu-opioid receptor by naltrexone produces a potent analgesic effect but no tolerance: role of mu-receptor activation and delta-receptor blockade in morphine tolerance. J Neurosci. 2005;25(12):3229–3233. doi: 10.1523/jneurosci.0332-05.2005. - DOI - PMC - PubMed
    1. Thompson BL, Oscar-Berman M, Kaplan GB. Opioid-induced structural and functional plasticity of medium-spiny neurons in the nucleus accumbens. Neurosci Biobehav Rev. 2021;120:417–430. doi: 10.1016/j.neubiorev.2020.10.015. - DOI - PMC - PubMed

Publication types

LinkOut - more resources