GWAS and meta-analysis identifies multiple new genetic mechanisms underlying severe Covid-19
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Pulmonary inflammation drives critical illness in Covid-19, 1;2 creating a clinically homogeneous extreme phenotype, which we have previously shown to be highly efficient for discovery of genetic associations. 3;4 Despite the advanced stage of illness, we have found that immunomodulatory therapies have strong beneficial effects in this group. 1;5 Further genetic discoveries may identify additional therapeutic targets to modulate severe disease. 6 In this new data release from the GenOMICC (Genetics Of Mortality in Critical Care) study we include new microarray genotyping data from additional critically-ill cases in the UK and Brazil, together with cohorts of severe Covid-19 from the ISARIC4C 7 and SCOURGE 8 studies, and meta-analysis with previously-reported data. We find an additional 14 new genetic associations. Many are in potentially druggable targets, in inflammatory signalling (JAK1, PDE4A), monocyte-macrophage differentiation (CSF2), immunometabolism (SLC2A5, AK5), and host factors required for viral entry and replication (TMPRSS2, RAB2A). As with our previous work, these results provide tractable therapeutic targets for modulation of harmful host-mediated inflammation in Covid-19.
Article activity feed
-
SciScore for 10.1101/2022.03.07.22271833: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Meta-analysis: All meta-analysis across studies were performed using an inverse-variance weighting method and control for population stratification in the METAL software 30. METALsuggested: (METAL, RRID:SCR_002013)Transcriptome-wide Association Studies: We performed TWAS in the MetaXcan framework and the GTExv8 eQTL and sQTL MASHR-M models available for download in http://predictdb.org/. MetaXcansuggested: NoneResults from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study …SciScore for 10.1101/2022.03.07.22271833: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Meta-analysis: All meta-analysis across studies were performed using an inverse-variance weighting method and control for population stratification in the METAL software 30. METALsuggested: (METAL, RRID:SCR_002013)Transcriptome-wide Association Studies: We performed TWAS in the MetaXcan framework and the GTExv8 eQTL and sQTL MASHR-M models available for download in http://predictdb.org/. MetaXcansuggested: NoneResults from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
-
