Bioinformatics analysis of potential pathogenesis and risk genes of immunoinflammation-promoted renal injury in severe COVID-19
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-1...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-08-01
|
| Series: | Frontiers in Immunology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2022.950076/full |
| _version_ | 1811321363478085632 |
|---|---|
| author | Zhimin Chen Zhimin Chen Caiming Chen Caiming Chen Fengbin Chen Ruilong Lan Guo Lin Yanfang Xu Yanfang Xu Yanfang Xu |
| author_facet | Zhimin Chen Zhimin Chen Caiming Chen Caiming Chen Fengbin Chen Ruilong Lan Guo Lin Yanfang Xu Yanfang Xu Yanfang Xu |
| author_sort | Zhimin Chen |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T13:16:18Z |
| format | Article |
| id | doaj.art-8aef6c910fa74ff79efbadc49eaa9f9a |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-04-13T13:16:18Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-8aef6c910fa74ff79efbadc49eaa9f9a2022-12-22T02:45:27ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-08-011310.3389/fimmu.2022.950076950076Bioinformatics analysis of potential pathogenesis and risk genes of immunoinflammation-promoted renal injury in severe COVID-19Zhimin Chen0Zhimin Chen1Caiming Chen2Caiming Chen3Fengbin Chen4Ruilong Lan5Guo Lin6Yanfang Xu7Yanfang Xu8Yanfang Xu9Department of Nephrology, Blood Purification Research Center, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaResearch Center for Metabolic Chronic Kidney Disease, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaDepartment of Nephrology, Blood Purification Research Center, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaResearch Center for Metabolic Chronic Kidney Disease, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaDepartment of Traditional Chinese Medicine, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaCentral Laboratory, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaDepartment of Intensive Care Unit, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaDepartment of Nephrology, Blood Purification Research Center, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaResearch Center for Metabolic Chronic Kidney Disease, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaCentral Laboratory, The First Affiliated Hospital, Fujian Medical University, Fuzhou, ChinaRenal 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.https://www.frontiersin.org/articles/10.3389/fimmu.2022.950076/fullCOVID-19renal injuryWGCNAnomogrambioinformaticsSTEM |
| spellingShingle | Zhimin Chen Zhimin Chen Caiming Chen Caiming Chen Fengbin Chen Ruilong Lan Guo Lin Yanfang Xu Yanfang Xu Yanfang Xu Bioinformatics analysis of potential pathogenesis and risk genes of immunoinflammation-promoted renal injury in severe COVID-19 Frontiers in Immunology COVID-19 renal injury WGCNA nomogram bioinformatics STEM |
| title | Bioinformatics analysis of potential pathogenesis and risk genes of immunoinflammation-promoted renal injury in severe COVID-19 |
| title_full | Bioinformatics analysis of potential pathogenesis and risk genes of immunoinflammation-promoted renal injury in severe COVID-19 |
| title_fullStr | Bioinformatics analysis of potential pathogenesis and risk genes of immunoinflammation-promoted renal injury in severe COVID-19 |
| title_full_unstemmed | Bioinformatics analysis of potential pathogenesis and risk genes of immunoinflammation-promoted renal injury in severe COVID-19 |
| title_short | Bioinformatics analysis of potential pathogenesis and risk genes of immunoinflammation-promoted renal injury in severe COVID-19 |
| title_sort | bioinformatics analysis of potential pathogenesis and risk genes of immunoinflammation promoted renal injury in severe covid 19 |
| topic | COVID-19 renal injury WGCNA nomogram bioinformatics STEM |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2022.950076/full |
| work_keys_str_mv | AT zhiminchen bioinformaticsanalysisofpotentialpathogenesisandriskgenesofimmunoinflammationpromotedrenalinjuryinseverecovid19 AT zhiminchen bioinformaticsanalysisofpotentialpathogenesisandriskgenesofimmunoinflammationpromotedrenalinjuryinseverecovid19 AT caimingchen bioinformaticsanalysisofpotentialpathogenesisandriskgenesofimmunoinflammationpromotedrenalinjuryinseverecovid19 AT caimingchen bioinformaticsanalysisofpotentialpathogenesisandriskgenesofimmunoinflammationpromotedrenalinjuryinseverecovid19 AT fengbinchen bioinformaticsanalysisofpotentialpathogenesisandriskgenesofimmunoinflammationpromotedrenalinjuryinseverecovid19 AT ruilonglan bioinformaticsanalysisofpotentialpathogenesisandriskgenesofimmunoinflammationpromotedrenalinjuryinseverecovid19 AT guolin bioinformaticsanalysisofpotentialpathogenesisandriskgenesofimmunoinflammationpromotedrenalinjuryinseverecovid19 AT yanfangxu bioinformaticsanalysisofpotentialpathogenesisandriskgenesofimmunoinflammationpromotedrenalinjuryinseverecovid19 AT yanfangxu bioinformaticsanalysisofpotentialpathogenesisandriskgenesofimmunoinflammationpromotedrenalinjuryinseverecovid19 AT yanfangxu bioinformaticsanalysisofpotentialpathogenesisandriskgenesofimmunoinflammationpromotedrenalinjuryinseverecovid19 |