Comprehensive bioinformatics analysis identifies hub genes associated with immune cell infiltration in early-onset schizophrenia.

IF 3.4 2区 医学 Q2 PSYCHIATRY
Shasha Wu, Tailian Xue, Yilin Li, Weikang Chen, Yan Ren
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引用次数: 0

Abstract

Background: Early-onset schizophrenia (EOS) occurs between the ages of 13 and 17 years, and neurobiological factors leading to cognitive deficits and psychotic symptoms with varying degrees of positive and negative symptoms. Numerous studies have demonstrated a broad link between immune dysregulation and the central nervous system in EOS, and its pathogenesis involves immune dysfunction, but the exact biological mechanisms have not been elucidated. This study employs immune infiltration analysis and bioinformatics to unveil the pathogenic mechanisms of EOS and identify potential diagnostic biomarkers, aiming for more precise clinical interventions.

Methods: In this study, we recruited 26 EOS patients and 27 healthy controls (HCs), and microarray data were collected. Crossover genes were identified using weighted gene co-expression network analysis (WGCNA) and differential expression genes (DEGs) analysis. These genes were subjected to genome enrichment analysis (GSEA) and gene ontology (GO) analysis. Hub genes were identified through protein-protein interactions (PPIs) and the GeneMANIA database. The diagnostic potential of immune-associated hub genes was evaluated using ROC analysis. Immune infiltration in EOS was analyzed with CIBERSORT. Regulatory miRNAs for the hub genes were predicted using miRNet, and the correlation between mRNAs and miRNAs was analyzed and validated in clinical samples.

Results: By WGCNA and DEGs analysis, 330 relevant genes were screened in EOS patients compared to HCs. Functional enrichment analysis using Metascape showed significant enrichment in immune system pathways. Subsequently, a PPI network was constructed to select the top 10 potential hub genes, and functional analysis was performed by GeneMANIA, resulting in the identification of four immune-related genes. In addition, significant differences were observed among the four immune cell types in the two groups of samples. ROC analysis showed clinical relevance of the immune-related hub genes, and the AUC of all genes was greater than 0.7. A miRNA-mRNA regulatory network was constructed from miRNA data, and three miRNAs were found to be significantly associated with the immune-related hub genes.

Conclusion: Our findings demonstrated that CCL3, IL1B, CXCL8, CXCL10 and miR-34a-5p may be biomarkers that play crucial roles in the underlying mechanisms of EOS immune-related pathways. These findings contribute to the understanding of EOS pathophysiology and may help identify new diagnostic and therapeutic targets.

综合生物信息学分析确定了早发性精神分裂症中与免疫细胞浸润相关的枢纽基因。
背景:早发性精神分裂症(EOS)发生在13 - 17岁之间,神经生物学因素导致认知缺陷和精神病症状,并伴有不同程度的阳性和阴性症状。大量研究表明,EOS的免疫失调与中枢神经系统存在广泛联系,其发病机制涉及免疫功能障碍,但确切的生物学机制尚未阐明。本研究采用免疫浸润分析和生物信息学方法,揭示EOS的发病机制,识别潜在的诊断生物标志物,旨在更精确地进行临床干预。方法:在本研究中,我们招募了26例EOS患者和27例健康对照(hc),并收集了微阵列数据。采用加权基因共表达网络分析(WGCNA)和差异表达基因(DEGs)分析鉴定交叉基因。对这些基因进行基因组富集分析(GSEA)和基因本体分析(GO)。Hub基因通过蛋白-蛋白相互作用(PPIs)和GeneMANIA数据库进行鉴定。使用ROC分析评估免疫相关中枢基因的诊断潜力。用CIBERSORT分析EOS的免疫浸润情况。使用miRNet预测枢纽基因的调控mirna,并在临床样本中分析和验证mrna与mirna之间的相关性。结果:通过WGCNA和DEGs分析,与hc相比,EOS患者中筛选出330个相关基因。metscape功能富集分析显示免疫系统通路中有显著富集。随后,构建PPI网络,筛选出10个潜在枢纽基因,并通过GeneMANIA进行功能分析,最终鉴定出4个免疫相关基因。此外,两组样品中四种免疫细胞类型之间存在显著差异。ROC分析显示免疫相关枢纽基因具有临床相关性,所有基因的AUC均大于0.7。利用miRNA数据构建了miRNA- mrna调控网络,发现3个miRNA与免疫相关中枢基因显著相关。结论:我们的研究结果表明,CCL3、IL1B、CXCL8、CXCL10和miR-34a-5p可能是在EOS免疫相关通路的潜在机制中发挥重要作用的生物标志物。这些发现有助于理解EOS的病理生理学,并可能有助于确定新的诊断和治疗靶点。
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来源期刊
BMC Psychiatry
BMC Psychiatry 医学-精神病学
CiteScore
5.90
自引率
4.50%
发文量
716
审稿时长
3-6 weeks
期刊介绍: BMC Psychiatry is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of psychiatric disorders, as well as related molecular genetics, pathophysiology, and epidemiology.
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