ArticleFrontiers in neuroscience2020
Identification and Characterization of Biomarkers and Their Role in Opioid Addiction by Integrated Bioinformatics Analysis.
Article in Frontiers in neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 9 citations in OpenAlex.
- Identification and validation of cellular senescence-related genes and immune cell infiltration characteristics in intervertebral disc degeneration.Frontiers in immunology · 2025Article
- Biomarker discovery using machine learning in the psychosis spectrum.Biomarkers in neuropsychiatry · 2024Article
- Identification of stress-induced epigenetic methylation onto dopamine D2 gene and neurological and behavioral consequences.Gene & protein in disease · 2024Article
- Multiscale topology in interactomic network: from transcriptome to antiaddiction drug repurposing.Briefings in bioinformatics · 2024Article
- Neuroimmune Mechanisms of Opioid Use Disorder and Recovery: Translatability to Human Studies, and Future Research Directions.Neuroscience · 2023Review
- Identification of key genes and therapeutic drugs for cocaine addiction using integrated bioinformatics analysis.Frontiers in neuroscience · 2023Article
- Inflammatory Biomarkers in Addictive Disorders.Biomolecules · 2021Review
- RNA-Seq Analysis of Morphine-Induced Gene Expression Changes in the Mouse Nucleus Accumbens.Iranian journal of pharmaceutical research : IJPRArticle
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although numerous studies have confirmed that the mechanisms of opiate addiction include genetic and epigenetic aspects, the results of such studies are inconsistent. Here, we downloaded gene expression profiling information, GSE87823, from the Gene Expression Omnibus database. Samples from males between ages 19 and 35 were selected for analysis of differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses were used to analyze the pathways associated with the DEGs. We further constructed protein-protein interaction (PPI) networks using the STRING database and used 10 different calculation methods to validate the hub genes. Finally, we utilized the Basic Local Alignment Search Tool (BLAST) to identify the DEG with the highest sequence similarity in mouse and detected the change in expression of the hub genes in this animal model using RT-qPCR. We identified three key genes,
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Registered trials
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