Psychopharmacology · 2024
Bioinformatics analysis of the mechanisms of traumatic brain injury-associated dementia based on the competing endogenous RNA.
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Cui Changmeng, Zhu Li, Han Guangkui, Sun Jianping, Zhang Liang, Guo Yujin, Jiang Pei
Аннотация
RATIONALE: Traumatic brain injury (TBI) is a critical condition associated with cognitive impairments, including dementia. This study is aimed to construct a long noncoding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) network based on bioinformatics analysis and explore molecular mechanisms underlying post-TBI dementia.
METHODS: GSE104687 and GSE205661 datasets were downloaded from Gene Expression Omnibus database. Molecular Signatures Database (MSigDB) was used to search oxidative stress-, metabolism- and immune-related genes as the target gene datasets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were carried out for functional annotation and enrichment analysis. A TBI mouse model was built to validate the expression of NF2, PLXNA2, NCBP2 and U2SURP in brain tissues.
RESULTS: A total of 7 differentially expressed lncRNAs (DElncRNAs) and 191 DEmRNAs were obtained. Subsequent to differential expression (DE) analysis, a lncRNA-miRNA-mRNA network was established. Notably, 13 key DEmRNAs were identified, potentially playing pivotal roles in the pathogenesis of TBI-induced dementia. By comparing the target gene datasets with 13 DEmRNAs, we identified 4 target genes that overlap with the 13 DEGmRNAs, namely NF2, PLXNA2, NCBP2 and U2SURP. Functional enrichment analysis highlighted the involvement of neuronal projections in the dementia-enriched cluster, while the protective cluster showed associations with protein synthesis and ubiquitination pathways. Importantly, we explored potential drug interventions based on interactions with the above 4 target genes. Additionally, drug interaction prediction showed that NF2 could interact with SELUMETINIB, EVEROLIMUS and TEMSIROLIMUS.
CONCLUSION: Our study provides insights into the complex regulatory networks underlying post-TBI dementia and suggests a potential role for three classes of drugs in managing dementia symptoms in TBI-induced dementia.
METHODS: GSE104687 and GSE205661 datasets were downloaded from Gene Expression Omnibus database. Molecular Signatures Database (MSigDB) was used to search oxidative stress-, metabolism- and immune-related genes as the target gene datasets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were carried out for functional annotation and enrichment analysis. A TBI mouse model was built to validate the expression of NF2, PLXNA2, NCBP2 and U2SURP in brain tissues.
RESULTS: A total of 7 differentially expressed lncRNAs (DElncRNAs) and 191 DEmRNAs were obtained. Subsequent to differential expression (DE) analysis, a lncRNA-miRNA-mRNA network was established. Notably, 13 key DEmRNAs were identified, potentially playing pivotal roles in the pathogenesis of TBI-induced dementia. By comparing the target gene datasets with 13 DEmRNAs, we identified 4 target genes that overlap with the 13 DEGmRNAs, namely NF2, PLXNA2, NCBP2 and U2SURP. Functional enrichment analysis highlighted the involvement of neuronal projections in the dementia-enriched cluster, while the protective cluster showed associations with protein synthesis and ubiquitination pathways. Importantly, we explored potential drug interventions based on interactions with the above 4 target genes. Additionally, drug interaction prediction showed that NF2 could interact with SELUMETINIB, EVEROLIMUS and TEMSIROLIMUS.
CONCLUSION: Our study provides insights into the complex regulatory networks underlying post-TBI dementia and suggests a potential role for three classes of drugs in managing dementia symptoms in TBI-induced dementia.