A catalog of associations between rare coding variants and COVID-19 outcomes

  1. J. A. Kosmicki
  2. J. E. Horowitz
  3. N. Banerjee
  4. R. Lanche
  5. A. Marcketta
  6. E. Maxwell
  7. X. Bai
  8. D. Sun
  9. J. D. Backman
  10. D. Sharma
  11. H. M. Kang
  12. C. O’Dushlaine
  13. A. Yadav
  14. A. J. Mansfield
  15. A. H. Li
  16. K. Watanabe
  17. L. Gurski
  18. S. E. McCarthy
  19. A. E. Locke
  20. S. Khalid
  21. S. O’Keeffe
  22. J. Mbatchou
  23. O. Chazara
  24. Y. Huang
  25. E. Kvikstad
  26. A. O’Neill
  27. P. Nioi
  28. M. M. Parker
  29. S. Petrovski
  30. H. Runz
  31. J. D. Szustakowski
  32. Q. Wang
  33. E. Wong
  34. A. Cordova-Palomera
  35. E. N. Smith
  36. S. Szalma
  37. X. Zheng
  38. S. Esmaeeli
  39. J. W. Davis
  40. Y-P. Lai
  41. X. Chen
  42. A. E. Justice
  43. J. B. Leader
  44. T. Mirshahi
  45. D. J. Carey
  46. A. Verma
  47. G. Sirugo
  48. M. D. Ritchie
  49. D. J. Rader
  50. G. Povysil
  51. D. B. Goldstein
  52. K. Kiryluk
  53. E. Pairo-Castineira
  54. K. Rawlik
  55. D. Pasko
  56. S. Walker
  57. A. Meynert
  58. A. Kousathanas
  59. L. Moutsianas
  60. A. Tenesa
  61. M. Caulfield
  62. R. Scott
  63. J. F. Wilson
  64. J. K. Baillie
  65. G. Butler-Laporte
  66. T. Nakanishi
  67. M. Lathrop
  68. J.B. Richards
  69. Regeneron Genetics Center
  70. UKB Exome Sequencing Consortium
  71. M. Jones
  72. S. Balasubramanian
  73. W. Salerno
  74. A. R. Shuldiner
  75. J. Marchini
  76. J. D. Overton
  77. L. Habegger
  78. M. N. Cantor
  79. J. G. Reid
  80. A. Baras
  81. G. R. Abecasis
  82. M. A. Ferreira

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Abstract

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-19 (COVID-19), a respiratory illness that can result in hospitalization or death. We investigated associations between rare genetic variants and seven COVID-19 outcomes in 543,213 individuals, including 8,248 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 14 interferon pathway genes in which rare deleterious variants have been reported in severe COVID-19 patients; (ii) 167 genes located in COVID-19 GWAS risk loci; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, with results publicly browsable at https://rgc-covid19.regeneron.com .

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  1. ScreenIT

    SciScore for 10.1101/2020.10.28.20221804: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Genotype data for variants not included in the arrays were then inferred using three reference panels (Haplotype Reference Consortium, UK10K and 1000 Genomes Project phase 3) as described previously [24].
    1000 Genomes Project
    suggested: (1000 Genomes Project and AWS, RRID:SCR_008801)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    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.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.10.28.20221804v2 on medRxiv
  4. Rapid Reviews Infectious Diseases

    Giuseppe Novelli

    Review 2: "Genetic association analysis of SARS-CoV-2 infection in 455,838 UK Biobank participants"

    The authors looked for the genetic loci of COVID-19 risk and severity in the UK biobank. Further studies are needed to pinpoint bona fide loci associated with COVID19 severity and susceptibility, though this study method is deemed reliable by reviewers.

  5. Rapid Reviews Infectious Diseases

    Jonathan Fischer

    Review 1: "Genetic association analysis of SARS-CoV-2 infection in 455,838 UK Biobank participants"

    The authors looked for the genetic loci of COVID-19 risk and severity in the UK biobank. Further studies are needed to pinpoint bona fide loci associated with COVID19 severity and susceptibility, though this study method is deemed reliable by reviewers.

  6. Version published to 10.1101/2020.10.28.20221804v1 on medRxiv