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Exploration of the Differentially Expressed Long Noncoding RNAs and Genes of Morphine Tolerance via Bioinformatic Analysis.
- Source :
-
Journal of computational biology : a journal of computational molecular cell biology [J Comput Biol] 2019 Dec; Vol. 26 (12), pp. 1379-1393. Date of Electronic Publication: 2019 Jul 10. - Publication Year :
- 2019
-
Abstract
- Morphine tolerance is one of the most common complications in patients with chronic pain. Many patients with morphine tolerance have poor efficacy in the treatment of primary pain, and are accompanied by the side effects. Previous studies have found that many mechanisms are involved in morphine tolerance, but few researches could fully explain morphine tolerance, and no effective treatment for morphine tolerance has been found. One expression profiling data set was downloaded from the Gene Expression Omnibus (GEO) database. The probes would be transformed into the homologous gene symbol by means of the platform's annotation information. GEO2R was used to search for differentially expressed long noncoding RNAs (lncRNAs) and differentially expressed genes (DEGs) that were differentially expressed between spinal cord samples. Receiver operator characteristic curve analysis was performed to determine the ability of the hub lncRNAs to predict morphine tolerance. Through the principal component analysis, the intragroup data repeatability is fine in the GSE110115. A total of 10 genes were identified as hub genes from the protein-protein interaction network with degrees ≥10. Compared with the normal saline group, the expression levels of LncRNA XR_006440, XR_009493, AF196267, MRAK150340, and MRAK037188 were more downregulated, while the expression levels of MRAK046606, XR_005988, DQ266361, uc.167-, and uc.468+ were more upregulated in the morphine tolerance group. LncRNAs and DEGs were differentially expressed between the morphine tolerance group and nonmorphine tolerance group, which may be involved in the development of morphine tolerance, especially LncRNA DQ266361, uc.167-, and Mmp9 , CCL7 genes.
- Subjects :
- Databases, Genetic
Gene Expression Profiling
Gene Ontology
Gene Regulatory Networks drug effects
Humans
Linear Models
Protein Interaction Maps drug effects
Protein Interaction Maps genetics
RNA, Long Noncoding metabolism
ROC Curve
Reproducibility of Results
Computational Biology
Gene Expression Regulation drug effects
Morphine pharmacology
RNA, Long Noncoding genetics
Subjects
Details
- Language :
- English
- ISSN :
- 1557-8666
- Volume :
- 26
- Issue :
- 12
- Database :
- MEDLINE
- Journal :
- Journal of computational biology : a journal of computational molecular cell biology
- Publication Type :
- Academic Journal
- Accession number :
- 31290683
- Full Text :
- https://doi.org/10.1089/cmb.2019.0188