Peng Lu, Wang Xiaodi, Bing Dan
Department of Otorhinolaryngology Head and Neck Surgery, Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
Department of Otorhinolaryngology Head and Neck Surgery, Second Affiliated Hospital of Guangxi Medical University, Nanning, China.
Front Genet. 2021 Nov 22;12:747576. doi: 10.3389/fgene.2021.747576. eCollection 2021.
Obstructive sleep apnea (OSA) is considered to be an independent factor affecting lipid metabolism. This study explored the relationship between immune genes and lipid metabolism in OSA. Immune-related Differentially Expressed Genes (DEGs) were identified by analyzing microarray data sets from the Gene Expression Omnibus (GEO) database. Subsequently, we conducted protein-protein interaction (PPI) network analysis and calculated their Gene Ontology (GO) semantic similarity. The GO, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, Disease Ontology (DO), gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were employed for functional enrichment analyses and to determine the most significant functional terms. Combined with the results of boruta and random forest, we selected predictors to build a prognostic model, along with seeking out the potential TFs and target drugs for the predictive genes. Immune-related DEGs included 64 genes upregulated and 98 genes downregulated. The enrichment analysis might closely associate with cell adhesion and T cell-mediated immunity pathways and there were many DEGs involved in lipid and atherosclerosis signaling pathways. The highest-ranking hub gene in PPI network have been reported lowly expressed in OSA. In line with the enrichment analysis, DO analysis reveal that respiratory diseases may be associated with OSA besides immune system disorders. Consistent with the result of the KEGG pathway, the analysis of GSVA revealed that the pro-inflammation pathways are associated with OSA. Monocytes and CD8 T cells were the predominant immune cells in adipose tissue. We built a prognostic model with the top six genes, and the prognostic genes were involved in the polarization of macrophage and differentiation of T lymphocyte subsets. In vivo experimental verification revealed that EPGN, LGR5, NCK1 and VIP were significantly down-regulated while PGRMC2 was significantly up-regulated in mouse model of OSA. Our study demonstrated strong associations between immune genes and the development of dyslipidemia in OSA. This work promoted the molecular mechanisms and potential targets for the regulation of lipid metabolism in OSA.
阻塞性睡眠呼吸暂停(OSA)被认为是影响脂质代谢的一个独立因素。本研究探讨了OSA中免疫基因与脂质代谢之间的关系。通过分析来自基因表达综合数据库(GEO)的微阵列数据集,确定了免疫相关差异表达基因(DEG)。随后,我们进行了蛋白质-蛋白质相互作用(PPI)网络分析,并计算了它们的基因本体(GO)语义相似性。使用GO、京都基因与基因组百科全书(KEGG)通路、疾病本体(DO)、基因集富集分析(GSEA)和基因集变异分析(GSVA)进行功能富集分析,并确定最显著的功能术语。结合博鲁塔和随机森林的结果,我们选择预测因子来构建预后模型,并寻找预测基因的潜在转录因子和靶向药物。免疫相关DEG包括64个上调基因和98个下调基因。富集分析可能与细胞黏附及T细胞介导的免疫通路密切相关,并且有许多DEG参与脂质和动脉粥样硬化信号通路。PPI网络中排名最高的枢纽基因在OSA中表达较低。与富集分析一致,DO分析表明,除免疫系统紊乱外,呼吸系统疾病可能与OSA有关。与KEGG通路结果一致,GSVA分析表明促炎通路与OSA有关。单核细胞和CD8 T细胞是脂肪组织中的主要免疫细胞。我们用前六个基因构建了一个预后模型,这些预后基因参与巨噬细胞极化和T淋巴细胞亚群分化。体内实验验证表明,在OSA小鼠模型中,EPGN、LGR5、NCK1和VIP显著下调,而PGRMC2显著上调。我们的研究证明了免疫基因与OSA中血脂异常的发生发展之间存在密切关联。这项工作促进了对OSA中脂质代谢调节的分子机制和潜在靶点的研究。