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基于凋亡相关基因构建精神分裂症诊断模型和 lncRNA 相关 ceRNA 网络

Construction of a Diagnostic Model and a lncRNA-Associated ceRNA Network Based on Apoptosis-Related Genes for Schizophrenia.

机构信息

Department of Psychiatry, Wuhan Mental Health Center, Wuhan, Hubei Province 430012, China.

Department of Sleep, Wuhan Hospital of Psychotherapy, Wuhan, Hubei Province, China.

出版信息

Behav Neurol. 2023 Jun 20;2023:7017106. doi: 10.1155/2023/7017106. eCollection 2023.

DOI:10.1155/2023/7017106
PMID:37383091
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10299887/
Abstract

METHODS

Gene expression profiles and apoptosis-related data were downloaded from the Gene Expression Omnibus and Molecular Signature databases, respectively. Apoptosis-related differentially expressed mRNAs (DEGs) and miRNAs (DEMs) from blood samples between the schizophrenia and healthy control individuals were screened. A diagnostic model was developed using the data from univariate and least absolute shrinkage and selection operator (LASSO) regression analyses, followed by validation using the GSE38485 dataset. Cases were divided into low-risk (LR) and high-risk (HR) groups based on the risk score of the model, and differences in immune gene sets and pathways between these two groups were compared. Finally, a ceRNA network was constructed by integrating long non-coding RNAs (lncRNAs), DEMs, and DEGs.

RESULTS

A diagnostic model containing 15 apoptosis-related genes was developed and its diagnostic efficiency was found to be robust. The HR group was correlated with higher immune scores of chemokines, cytokines, and interleukins; it was also significantly involved in pathways such as pancreatic beta cells and early estrogen response. A ceRNA network composed of 2 lncRNAs, 14 miRNAs, and 5 mRNAs was established.

CONCLUSIONS

The established model is a potential tool to improve the diagnostic efficiency of patients with schizophrenia, and the nodes included in the ceRNA network might serve as biomarkers and therapeutic targets for schizophrenia.

摘要

方法

分别从基因表达综合数据库和分子特征数据库下载基因表达谱和与凋亡相关的数据。筛选精神分裂症患者和健康对照个体血液样本中与凋亡相关的差异表达的 mRNA（DEGs）和 microRNA（DEMs）。使用单变量和最小绝对值收缩和选择算子（LASSO）回归分析的数据开发诊断模型，然后使用 GSE38485 数据集进行验证。根据模型的风险评分将病例分为低风险（LR）和高风险（HR）组，并比较两组之间免疫基因集和途径的差异。最后，通过整合长链非编码 RNA（lncRNA）、DEMs 和 DEGs 构建 ceRNA 网络。

结果

开发了包含 15 个与凋亡相关的基因的诊断模型，其诊断效率被发现是稳健的。HR 组与趋化因子、细胞因子和白细胞介素的更高免疫评分相关；它还显著参与了胰腺β细胞和早期雌激素反应等途径。建立了一个由 2 个 lncRNA、14 个 miRNA 和 5 个 mRNA 组成的 ceRNA 网络。

结论

所建立的模型是提高精神分裂症患者诊断效率的潜在工具，ceRNA 网络中包含的节点可能作为精神分裂症的生物标志物和治疗靶点。

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