Molecular mechanism and candidate biomarkers of morphine for analgesia and addiction effects

BACKGROUND: Morphine and its substitutes are frequently used in the clinical treatment of acute severe pain and advanced cancer patients. Long-term irregular use of morphine will lead to severe dependence. However, the genes behind the analgesic and addictive effects of morphine still need to be revealed. METHODS: We retrieved and downloaded RNA expression data sets related to morphine pain and addiction effects from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes. Functional enrichment analysis was performed to analyze relevant pathways. Gene expression trends was used to screen key genes associated with addiction effects. miRNAs and PPIs were used to explore the functional mechanisms of genes. RESULTS: A total of 163 up-regulated and 277 down-regulated genes were obtained in the dataset for analgesic effects. A total of 1,482 up-regulated and 1,754 down-regulated differentially expressed genes (DEGs) were obtained in the dataset for addictive effects. By taking the intersection, 8 up-regulated and 22 down-regulated mRNAs which showed high correlations with both analgesic and addictive effects were identified. Based on the DEGs, a comprehensive network combining the mRNA-miRNA network and protein-protein interaction (PPI) network was established. Among the networks, 1 up-regulated miRNA (miR-129) and 3 down-regulated miRNAs (miR-714, miR-2135, and miR-2145) were identified. Gene expression trends and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms indicated that Fos may be a biomarker for morphine addiction. CONCLUSIONS: Our findings will provide a valuable foundation for future genetic mechanism studies of the analgesic and addictive effects of morphine and provide inspiration for finding analgesic substitutes and relieving the addiction of analgesic drugs.