The NRF1/miR-4514/SOCS3 Pathway Is Associated with Schizophrenia Pathogenesis

Yilin Liu, Shujun Li, Xiao Ma, Q. Long, Lei Yu, Yatang Chen, Wenzhi Wu, Z. Guo, Z. Teng, Yong Zeng
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Abstract

Background: Schizophrenia (SZ) is a common and severe mental disease. However, its etiology and pathogenesis have not been fully established. In this study, bioinformatics was used to identify SZ-related genes and reveal the potential mechanisms of them. Methods: Gene expression profiles were obtained from the GSE46509 dataset. Differentially expressed genes (DEGs) were analyzed by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment databases. A protein-protein interaction (PPI) network was established. TargetScan and miRGen, which are based on bioinformatics algorithms, were used to predict potential candidate target miRNAs and transcription factors. Results: Compared to healthy people controls, a total of 1422 DEGs were identified in SZ patient samples. Functional enrichment analysis revealed that these DEGs were significantly enriched in RNA processing, mRNA binding, and cell adhesion molecules. In addition, in the PPI network, SOCS3, FBXO9, ASB17, FBXO10, and ASB4 were identified as hub genes. In the predicted TF-miRNA-mRNA targeting regulatory network, hsa-miR-4514 was up-regulated by the highly expressed transcription factor (TF) NRF1, which down-regulated multiple hubs genes such as SOCS3, FBXO9, and FBXO10. Conclusions: Several potential biomarkers involved in SZ development were identified by bioinformatics analyses. Furthermore, our findings revealed the underpinning mechanisms of these potential biomarkers in the pathogenesis of SZ. And these results suggest a potential application value in clinical practice.
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NRF1/miR-4514/SOCS3通路与精神分裂症发病机制相关
背景:精神分裂症(Schizophrenia, SZ)是一种常见且严重的精神疾病。然而,其病因和发病机制尚未完全确定。本研究采用生物信息学方法鉴定sz相关基因,并揭示其潜在的作用机制。方法:从GSE46509数据集中获取基因表达谱。差异表达基因(DEGs)通过基因本体(GO)和京都基因与基因组百科全书(KEGG)途径富集数据库进行分析。建立了蛋白-蛋白相互作用(PPI)网络。TargetScan和miRGen基于生物信息学算法,用于预测潜在的候选靶标mirna和转录因子。结果:与健康对照者相比,在SZ患者样本中共鉴定出1422个deg。功能富集分析显示,这些deg在RNA加工、mRNA结合和细胞粘附分子中显著富集。此外,在PPI网络中,SOCS3、FBXO9、ASB17、FBXO10和ASB4被鉴定为枢纽基因。在预测的TF- mirna - mrna靶向调控网络中,高表达转录因子(TF) NRF1上调hsa-miR-4514,下调SOCS3、FBXO9和FBXO10等多个枢纽基因。结论:通过生物信息学分析确定了几个潜在的参与SZ发育的生物标志物。此外,我们的研究结果揭示了这些潜在生物标志物在SZ发病机制中的基本机制。这些结果在临床实践中具有潜在的应用价值。
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