Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1038/s41436-021-01243-5 http://scihub22266oqcxt.onion/10.1038/s41436-021-01243-5 34183789!8237048!34183789     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Genet+Med 2021 ; 23 (11): 2076-2086 Nephropedia Template TP {{tp|p=34183789|t=2021. An integrative multiomics analysis identifies putative causal genes for COVID-19 severity |pdf=|usr=}}{{34183789}} gab.com Text An integrative multiomics analysis identifies putative causal genes for COVID-19 severity JO: Genet Med http://www.kidney.de/pget.php?&tw=1&pmid=34183789 #FOAvip PURPOSE: It is critical to identify putative causal targets for SARS coronavirus 2, which may guide drug repurposing options to reduce the public health burden of COVID-19. METHODS: We applied complementary methods and multiphased design to pinpoint the most likely causal genes for COVID-19 severity. First, we applied cross-methylome omnibus (CMO) test and leveraged data from the COVID-19 Host Genetics Initiative (HGI) comparing 9,986 hospitalized COVID-19 patients and 1,877,672 population controls. Second, we evaluated associations using the complementary S-PrediXcan method and leveraging blood and lung tissue gene expression prediction models. Third, we assessed associations of the identified genes with another COVID-19 phenotype, comparing very severe respiratory confirmed COVID versus population controls. Finally, we applied a fine-mapping method, fine-mapping of gene sets (FOGS), to prioritize putative causal genes. RESULTS: Through analyses of the COVID-19 HGI using complementary CMO and S-PrediXcan methods along with fine-mapping, XCR1, CCR2, SACM1L, OAS3, NSF, WNT3, NAPSA, and IFNAR2 are identified as putative causal genes for COVID-19 severity. CONCLUSION: We identified eight genes at five genomic loci as putative causal genes for COVID-19 severity. Twit Text FOAVip An integrative multiomics analysis identifies putative causal genes for COVID-19 severity ????Genet Med http://www.kidney.de/pget.php?&tw=1&pmid=34183789 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34183789 #FOAvip English Wikipedia <ref>{{Cite pmid|34183789}}</ref> An integrative multiomics analysis identifies putative causal genes for COVID-19 severity #MMPMID34183789 Wu L; Zhu J; Liu D; Sun Y; Wu C Genet Med 2021[Nov]; 23 (11): 2076-2086 PMID34183789show ga PURPOSE: It is critical to identify putative causal targets for SARS coronavirus 2, which may guide drug repurposing options to reduce the public health burden of COVID-19. METHODS: We applied complementary methods and multiphased design to pinpoint the most likely causal genes for COVID-19 severity. First, we applied cross-methylome omnibus (CMO) test and leveraged data from the COVID-19 Host Genetics Initiative (HGI) comparing 9,986 hospitalized COVID-19 patients and 1,877,672 population controls. Second, we evaluated associations using the complementary S-PrediXcan method and leveraging blood and lung tissue gene expression prediction models. Third, we assessed associations of the identified genes with another COVID-19 phenotype, comparing very severe respiratory confirmed COVID versus population controls. Finally, we applied a fine-mapping method, fine-mapping of gene sets (FOGS), to prioritize putative causal genes. RESULTS: Through analyses of the COVID-19 HGI using complementary CMO and S-PrediXcan methods along with fine-mapping, XCR1, CCR2, SACM1L, OAS3, NSF, WNT3, NAPSA, and IFNAR2 are identified as putative causal genes for COVID-19 severity. CONCLUSION: We identified eight genes at five genomic loci as putative causal genes for COVID-19 severity. |*COVID-19[MESH] |Gene Expression[MESH] |Genome-Wide Association Study[MESH] |Humans[MESH] |Phenotype[MESH]An integrative multiomics analysis identifies putative causal genes fo(epmc).pdf DeepDyve Pubget Overpricing