目的:研究时钟基因与重度抑郁障碍(MDD)的关系。
方法:使用GEO数据库获取GSE98793、GSE39653和GSE52790的芯片数据和临床信息。通过分析MDD与健康对照之间的差异表达基因,发现了差异表达的时钟基因。对差异表达的时钟基因进行了基因本体论(GO)和京都基因和基因组途径(KEGG)富集分析。套索回归和支持向量机(SVM)方法用于筛选差异表达的时钟基因。利用筛选出的基因,采用Logistic回归建立抑郁症的诊断模型。采用接收器工作特性(ROC)曲线对模型进行验证。在诊断模型中对高得分的MDD和低得分的MDD进行基因差异表达分析。对差异表达的基因进行基因组富集分析(GSEA)富集分析。单基因GSEA用于分别分析模型中的每个基因。采用Cibersort方法分析MDD和健康对照的免疫浸润情况,并分析了免疫细胞与时钟基因之间的相关性。使用Cytoscape分析时钟基因相互作用网络。DGIdb网站用于预测与MDD密切相关的时钟基因的潜在有效治疗药物。
结果:通过对MDD和健康对照之间的时钟基因的差异表达分析,鉴定了六个基因。对6个基因的GO和KEGG富集分析表明,它们的通路集中于昼夜节律,有节奏的过程,TGF-β信号通路,长寿调节途径-多种物种,脂肪细胞因子信号通路等。Lasso回归和SVM用于筛选MDD的5个时钟基因(HDAC1,ID3,NFIL3,PRKAA1,TNF)。根据5个时钟基因建立抑郁症的诊断模型。建立的抑郁症诊断模型的曲线下面积(AUC)为0.686。对时钟基因诊断模型评分高的MDD患者和评分低的MDD患者进行基因差异分析。对差异基因进行GSEA显示,最富集的途径是:脂肪细胞因子信号通路,TGFβ信号通路,氧化磷酸化,原发性免疫缺陷,等等。单基因GSEA显示富集途径最多的是Toll样受体信号通路,糖脂代谢,氨基酸代谢,神经活性配体受体相互作用,等等。免疫浸润分析结果表明,NK细胞静息和巨噬细胞M2在MDD组和对照组之间存在差异。在MDD中,与NK细胞静息密切相关的基因是HDAC1,与巨噬细胞M2密切相关的基因是HDAC1和NFIL3。时钟基因的RNA相互作用网络表明其调控过程是复杂的,为后续相关研究提供参考。潜在的治疗药物预测显示,在5个时钟基因中,TNF,HDAC1和PRKAA1可能具有潜在的有效治疗药物。
结论:在所有CLOCK基因中,HDAC1、ID3、NFIL3、PRKAA1、TNF与MDD亲密相干。其中,TNF,HDAC1和PRKAA1可能具有潜在的有效治疗药物。
To
study the relationship between clock genes and Major Depressive Disorder (MDD).
GEO database was used to obtain the chip data and clinical information of datasets GSE98793, GSE39653 and GSE52790. The differentially expressed clock genes were found through the analysis of the differentially expressed genes between MDD and healthy controls. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes Pathway (KEGG) enrichment analysis were performed on the differential expressed clock genes. Lasso Regression and Support Vector Machine (SVM) method were used for screening the differential expressed clock genes. Logistic regression was used to establish a diagnostic model for depression with the screened genes. Receiver Operating Characteristic (ROC) Curve was used to verify the model. Gene differential expression analysis was performed for MDD with high scores and MDD with low scores in the diagnostic model. Gene Set Enrichment Analysis (GSEA) enrichment analysis was performed for differentially expressed genes. Single-gene GSEA was used to analyze each gene in the model separately. Cibersort method was used to analyze the immune infiltration of MDD and healthy controls, and the correlation between immune cells and clock genes was analyzed. Cytoscape was used to analyze the clock gene interaction network. The DGIdb website was used to predict potentially effective therapeutic drugs for clock genes closely related to MDD.
Six genes were identified by differential expression analysis of clock genes between MDD and healthy controls. GO and KEGG enrichment analysis of 6 genes showed that their pathways were concentrated such as circadian rhythm, rhythmic process, TGF - beta signaling pathway, longevity regulating pathway-multiple species, adipocytokine signaling pathway and so on. Lasso regression and SVM were used to screen out 5 clock genes (HDAC1, ID3, NFIL3, PRKAA1, TNF) for MDD. The diagnostic model of depression was established according to the 5 clock genes. The area under the curve (AUC) of the established depression diagnostic model was 0.686. Gene difference analysis was performed between MDD patients with high score of clock gene diagnostic model and MDD patients with low score. GSEA was performed for the differential genes showed that the most enriched pathways were:adipocytokine signaling pathway, TGF beta signaling pathway, oxidative phosphorylation, primary immunodeficiency, and so on. The single gene GSEA showed that the most enriched pathways were Toll like receptor signaling pathway, glucolipid metabolism, amino acid metabolism, neuroactive ligand receptor interaction, and so on. The results of immune infiltration analysis showed that NK cells resting and Macrophages M2 were different between MDD and control groups. In MDD, the gene closely related to NK cells resting was HDAC1, and the genes closely related to Macrophages M2 were
HDAC1 and NFIL3. The RNA interactions network of clock genes shows that the regulation process is complex, which can provide a reference for subsequent related research. Potential therapeutic drugs predict display, among the 5 clock genes, TNF,
HDAC1, and PRKAA1 may have potential effective therapeutic drugs.
Among all CLOCK genes,
HDAC1, ID3, NFIL3, PRKAA1, TNF are closely related to MDD. Among them, TNF,
HDAC1, and PRKAA1 may have potential effective therapeutic drugs.