4.8 Article

Integrative genomic analyses identify susceptibility genes underlying COVID-19 hospitalization

Journal

NATURE COMMUNICATIONS
Volume 12, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41467-021-24824-z

Keywords

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Funding

  1. NIH [S10OD017985, S10RR025141, R21 280 DC018098, R21 DA047527, F32 MH122058, U54MD010722-04, R01MH113362, R01MH118223, R56MH120736]
  2. National Center for Advancing Translational Sciences [UL1TR002243, UL1TR000445, UL1RR024975]
  3. National Human Genome Research Institute, NHGRI [T32 HG008341]
  4. National Institute of Health, NIGMS [R01GM140287]
  5. [U01HG004798]
  6. [R01NS032830]
  7. [RC2GM092618]
  8. [P50GM115305]
  9. [U01HG006378]
  10. [U19HL065962]
  11. [R01HD074711]

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This study integrates genome-wide association study data with mRNA expression, splicing, and protein levels to identify genes and pathways related to COVID-19 hospitalization, highlighting putative causal genes impacting disease severity and symptomology.
Despite rapid progress in characterizing the role of host genetics in SARS-Cov-2 infection, there is limited understanding of genes and pathways that contribute to COVID-19. Here, we integrate a genome-wide association study of COVID-19 hospitalization (7,885 cases and 961,804 controls from COVID-19 Host Genetics Initiative) with mRNA expression, splicing, and protein levels (n=18,502). We identify 27 genes related to inflammation and coagulation pathways whose genetically predicted expression was associated with COVID-19 hospitalization. We functionally characterize the 27 genes using phenome- and laboratory-wide association scans in Vanderbilt Biobank (n=85,460) and identified coagulation-related clinical symptoms, immunologic, and blood-cell-related biomarkers. We replicate these findings across trans-ethnic studies and observed consistent effects in individuals of diverse ancestral backgrounds in Vanderbilt Biobank, pan-UK Biobank, and Biobank Japan. Our study highlights and reconfirms putative causal genes impacting COVID-19 severity and symptomology through the host inflammatory response. Genome-wide association studies of COVID-19 have identified genetic loci affecting disease severity, but the mechanisms remain to be fully described. Here, the authors use genetically predicted transcriptome, splicing and proteome data to identify potential genes and pathways underlying COVID- 19 severity.

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