Department of Nephrology, Blood Purification Research Center, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Research Center for Metabolic Chronic Kidney Disease, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Front Immunol. 2022 Aug 16;13:950076. doi: 10.3389/fimmu.2022.950076. eCollection 2022.
Renal injury secondary to COVID-19 is an important factor for the poor prognosis of COVID-19 patients. The pathogenesis of renal injury caused by aberrant immune inflammatory of COVID-19 remains unclear. In this study, a total of 166 samples from 4 peripheral blood transcriptomic datasets of COVID-19 patients were integrated. By using the weighted gene co-expression network (WGCNA) algorithm, we identified key genes for mild, moderate, and severe COVID-19. Subsequently, taking these genes as input genes, we performed Short Time-series Expression Miner (STEM) analysis in a time consecutive ischemia-reperfusion injury (IRI) -kidney dataset to identify genes associated with renal injury in COVID-19. The results showed that only in severe COVID-19 there exist a small group of genes associated with the progression of renal injury. Gene enrichment analysis revealed that these genes are involved in extensive immune inflammation and cell death-related pathways. A further protein-protein interaction (PPI) network analysis screened 15 PPI-hub genes: , , , , , and . Single-cell sequencing analysis indicated that PPI-hub genes were mainly distributed in neutrophils, macrophages, and dendritic cells. Intercellular ligand-receptor analysis characterized the activated ligand-receptors between these immune cells and parenchyma cells in depth. And KEGG enrichment analysis revealed that viral protein interaction with cytokine and cytokine receptor, necroptosis, and Toll-like receptor signaling pathway may be potentially essential for immune cell infiltration leading to COVID-19 renal injury. Finally, we validated the expression pattern of PPI-hub genes in an independent data set by random forest. In addition, we found that the high expression of these genes was correlated with a low glomerular filtration rate. Including them as risk genes in lasso regression, we constructed a Nomogram model for predicting severe COVID-19. In conclusion, our study explores the pathogenesis of renal injury promoted by immunoinflammatory in severe COVID-19 and extends the clinical utility of its key genes.
新冠病毒导致的肾损伤是新冠患者预后不良的一个重要因素。新冠病毒引起的免疫炎症异常导致的肾损伤的发病机制尚不清楚。在本研究中，综合了来自 4 个新冠患者外周血转录组数据集的 166 个样本。我们使用加权基因共表达网络（WGCNA）算法，鉴定了轻、中、重度新冠患者的关键基因。随后，我们以这些基因作为输入基因，在一个时间连续的缺血再灌注损伤（IRI）-肾数据集上进行短时间序列表达挖掘（STEM）分析，以鉴定与新冠肾损伤相关的基因。结果表明，只有在重度新冠患者中，存在一小部分与肾损伤进展相关的基因。基因富集分析表明，这些基因涉及广泛的免疫炎症和细胞死亡相关途径。进一步的蛋白质-蛋白质相互作用（PPI）网络分析筛选出 15 个 PPI 枢纽基因：、、、、、和。单细胞测序分析表明，PPI 枢纽基因主要分布在中性粒细胞、巨噬细胞和树突状细胞中。细胞间配体-受体分析深入描述了这些免疫细胞与实质细胞之间激活的配体-受体。KEGG 富集分析表明，病毒蛋白与细胞因子和细胞因子受体的相互作用、坏死性凋亡和 Toll 样受体信号通路可能是导致新冠肾损伤的免疫细胞浸润的潜在关键因素。最后，我们通过随机森林在一个独立数据集上验证了 PPI 枢纽基因的表达模式。此外，我们发现这些基因的高表达与肾小球滤过率降低相关。将它们作为lasso 回归中的风险基因，我们构建了一个用于预测重症新冠的诺莫图模型。总之，我们的研究探讨了重症新冠中免疫炎症促进肾损伤的发病机制，并扩展了其关键基因的临床应用。
