Bioinformatics analysis of potential pathogenesis and risk genes of immunoinflammation-promoted renal injury in severe COVID-19

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.

Unraveling the mechanism of action of cepharanthine for the treatment of novel coronavirus pneumonia (COVID-19) from the perspectives of systematic pharmacology

“…LYN is Tyrosine-protein kinase Lyn, which plays an important role in the developmental maturation of B cells, the positive and negative regulation of inflammatory responses and the co-catalysis of T cells ( Brian and Freedman, 2021 ). LYN has been less studied in relation to COVID-19, but recent related studies have shown that LYN has an important relationship with severe COVID-19 ( Chen et al, 2022 ). HCK is the tyrosine protein kinase HCK, which plays an important role in hemopoiesis, regulation of the innate immune response and release of inflammatory molecules ( Podar et al, 2004 ).…”

“…HCK is the tyrosine protein kinase HCK, which plays an important role in hemopoiesis, regulation of the innate immune response and release of inflammatory molecules ( Podar et al, 2004 ). HCK has been identified as an important pharmacological target for improving lung function in patients with COVID-19 and has been significantly associated with COVID-19 in studies comparing healthy individuals with patients with severe COVID-19 ( Chen et al, 2022 , Chakraborty et al, 2021 ). In short, the selected hub targets elucidate the pharmacological mechanisms of action of cepharanthine for the treatment of COVID-19 at the level of antiviral, organismal metabolism, anticoagulation, and regulation of inflammatory and immune responses.…”

CXCL10 May Be Responsible for Susceptibility to Pulmonary Embolism in COVID-19 Patients

“…Previous studies have indicated that SARS-CoV-2 infection can cause a myriad of complications because there are common genes between COVID-19 and these complications. 23–26 Therefore, this study aimed to explore the possible genetic relationship between COVID-19 and PE through bioinformatics to reveal the underlying pathogenesis of susceptibility to PE events in COVID-19 patients.…”

Integrated Transcriptomics and Network Analysis of Potential Mechanisms and Health Effects of Convalescent COVID-19 Patients

“…Innovative bioinformatics approaches have been employed to determine the association between gastrointestinal and cardiovascular diseases and COVID-19 infection. 7 In this regard, transcriptome analyses of non-coding and coding elements should be able to identify risk factors at the molecular level that can be used to identify individuals that are likely to develop severe COVID-19, thus allowing for the development of early intervention strategies and customized therapeutic options. 8 Gene expression profiling has been conducted in individuals infected with SARS-CoV-2 to characterize the association of certain gene expression patterns with the disease.…”