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10.26355/eurrev_202110_27015 http://scihub22266oqcxt.onion/10.26355/eurrev_202110_27015 34730223!ä!34730223 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Eur+Rev+Med+Pharmacol+Sci 2021 ; 25 (20): 6411-6424 Nephropedia Template TP {{tp|p=34730223|t=2021. Identification of hub genes and molecular subtypes in COVID-19 based on WGCNA |pdf=|usr=}}{{34730223}} gab.com Text Identification of hub genes and molecular subtypes in COVID-19 based on WGCNA JO: Eur Rev Med Pharmacol Sci http://www.kidney.de/pget.php?&tw=1&pmid=34730223 #FOAvip OBJECTIVE: The heterogeneity of clinical manifestations and mortality rates in Coronavirus disease 2019 (COVID-19) patients may be related to the existence of molecular subtypes in COVID-19. To improve current management, it is essential to find the hub genes and pathways associated with different COVID-19 subtypes. MATERIALS AND METHODS: The whole-genome sequencing information (GSE156063, GSE163151) of nasopharyngeal swabs from normal subjects and COVID-19 patients were downloaded from the Gene Expression Omnibus (GEO) database. The molecular subtypes of patients with COVID-19 were classified using the "consistent clustering" method, and the specific genes associated with each subtype were found. Differentially expressed genes (DEGs) were screened between normal subjects and COVID-19 patients; the Weighted gene co-expression network analysis (WGCNA) method was used to find the key module genes of COVID-19 patients. Subtype-specific, differentially expressed and module-related genes were collected and intersected. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were carried out and protein-protein interaction (PPI) networks were generated. The pathways enriched in COVID-19 subtypes were analyzed by gene set variation analysis (GSVA). RESULTS: Patients with COVID-19 were divided into three subtypes, and there was no significant difference in gender and age distribution between subtypes. 82 differential gene pathways were screened between Subtypes I and II, 131 differential gene pathways were screened between Subtypes I and III, and 107 differential gene pathways were screened between Subtypes II and III. Finally, 44 differentially expressed key genes were screened, including 11 hub genes (RSAD2, IFIT1, MX1, OAS1, OAS2, BST2, IFI27, IFI35, IFI6, IFITM3, STAT2). CONCLUSIONS: There are significant differences in gene activation and pathway enrichment among different molecular subtypes of COVID-19, which may account for the heterogeneity in clinical presentation and the prognosis of patients. Twit Text FOAVip Identification of hub genes and molecular subtypes in COVID-19 based on WGCNA ????Eur Rev Med Pharmacol Sci http://www.kidney.de/pget.php?&tw=1&pmid=34730223 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34730223 #FOAvip English Wikipedia <ref>{{Cite pmid|34730223}}</ref> Identification of hub genes and molecular subtypes in COVID-19 based on WGCNA #MMPMID34730223 Hu RW; Liu C; Yan YY; Li D Eur Rev Med Pharmacol Sci 2021[Oct]; 25 (20): 6411-6424 PMID34730223show ga OBJECTIVE: The heterogeneity of clinical manifestations and mortality rates in Coronavirus disease 2019 (COVID-19) patients may be related to the existence of molecular subtypes in COVID-19. To improve current management, it is essential to find the hub genes and pathways associated with different COVID-19 subtypes. MATERIALS AND METHODS: The whole-genome sequencing information (GSE156063, GSE163151) of nasopharyngeal swabs from normal subjects and COVID-19 patients were downloaded from the Gene Expression Omnibus (GEO) database. The molecular subtypes of patients with COVID-19 were classified using the "consistent clustering" method, and the specific genes associated with each subtype were found. Differentially expressed genes (DEGs) were screened between normal subjects and COVID-19 patients; the Weighted gene co-expression network analysis (WGCNA) method was used to find the key module genes of COVID-19 patients. Subtype-specific, differentially expressed and module-related genes were collected and intersected. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were carried out and protein-protein interaction (PPI) networks were generated. The pathways enriched in COVID-19 subtypes were analyzed by gene set variation analysis (GSVA). RESULTS: Patients with COVID-19 were divided into three subtypes, and there was no significant difference in gender and age distribution between subtypes. 82 differential gene pathways were screened between Subtypes I and II, 131 differential gene pathways were screened between Subtypes I and III, and 107 differential gene pathways were screened between Subtypes II and III. Finally, 44 differentially expressed key genes were screened, including 11 hub genes (RSAD2, IFIT1, MX1, OAS1, OAS2, BST2, IFI27, IFI35, IFI6, IFITM3, STAT2). CONCLUSIONS: There are significant differences in gene activation and pathway enrichment among different molecular subtypes of COVID-19, which may account for the heterogeneity in clinical presentation and the prognosis of patients. |*Oligonucleotide Array Sequence Analysis[MESH] |Biomarkers, Tumor/*genetics[MESH] |COVID-19/diagnosis/*genetics[MESH] |Genetic Variation/genetics[MESH]Identification of hub genes and molecular subtypes in COVID-19 based o(epmc).pdf DeepDyve Pubget Overpricing