Abstract
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: ALOX5 , CD38 , GSF3R , LGR , RPR1 , HCK, ITGAX, LYN, MAPK3, NCF4, SELP, SPI1, WAS, TLR2 and TLR4 . 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.
Keywords: COVID-19; STEM; WGCNA; bioinformatics; nomogram; renal injury.
【저자키워드】 COVID-19, bioinformatics, nomogram, WGCNA, renal injury., STEM, 【초록키워드】 Neutrophils, Inflammation, Pathogenesis, macrophages, severe COVID-19, TLR4, risk, cytokine, progression, dendritic cells, immune, Peripheral blood, Immune cell infiltration, Algorithm, pathway, Mild, network analysis, dataset, expression, enrichment analysis, moderate, protein-protein interaction, CD38, COVID-19 patients, glomerular filtration rate, Interaction, gene co-expression network, Analysis, PPI, Inflammatory, Immune cell, Pathways, Injury, COVID-19 patient, necroptosis, Viral protein, poor prognosis, clinical utility, TLR2, KEGG, MAPK3, renal, random, cytokine receptor, expression pattern, Sequencing analysis, independent data set, SELP, toll-like receptor signaling, Genes, transcriptomic, Cell, ischemia-reperfusion injury, ALOX5, identify, performed, caused, involved, indicated, addition, screened, characterized, activated, correlated, promoted, HCK, Including, ITGAX, LYN, Miner, NCF4, SPI1, 【제목키워드】 Pathogenesis, severe COVID-19, risk, Analysis, Injury, renal,