tetano
Editor, Senior Moderator
Genet Med
. 2021 Jun 28.
doi: 10.1038/s41436-021-01243-5. Online ahead of print.
An integrative multiomics analysis identifies putative causal genes for COVID-19 severity
Lang Wu[SUP] #[/SUP][SUP] 1 [/SUP], Jingjing Zhu[SUP] #[/SUP][SUP] 2 [/SUP], Duo Liu[SUP] 2 3 [/SUP], Yanfa Sun[SUP] 2 4 5 6 [/SUP], Chong Wu[SUP] 7 [/SUP]
Affiliations
Abstract
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.
. 2021 Jun 28.
doi: 10.1038/s41436-021-01243-5. Online ahead of print.
An integrative multiomics analysis identifies putative causal genes for COVID-19 severity
Lang Wu[SUP] #[/SUP][SUP] 1 [/SUP], Jingjing Zhu[SUP] #[/SUP][SUP] 2 [/SUP], Duo Liu[SUP] 2 3 [/SUP], Yanfa Sun[SUP] 2 4 5 6 [/SUP], Chong Wu[SUP] 7 [/SUP]
Affiliations
- PMID: 34183789
- DOI: 10.1038/s41436-021-01243-5
Abstract
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.