Genetic mechanisms of critical illness in COVID-19

  1. The GenOMICC Investigators
  2. The ISARIC4C Investigators
  3. The COVID-19 Human Genetics Initiative
  4. 23andMe Investigators
  5. BRACOVID Investigators
  6. Gen-COVID Investigators
  7. Erola Pairo-Castineira
  8. Sara Clohisey
  9. Lucija Klaric
  10. Andrew D. Bretherick
  11. Konrad Rawlik
  12. Dorota Pasko
  13. Susan Walker
  14. Nick Parkinson
  15. Max Head Fourman
  16. Clark D. Russell
  17. James Furniss
  18. Anne Richmond
  19. Elvina Gountouna
  20. Nicola Wrobel
  21. David Harrison
  22. Bo Wang
  23. Yang Wu
  24. Alison Meynert
  25. Fiona Griffiths
  26. Wilna Oosthuyzen
  27. Athanasios Kousathanas
  28. Loukas Moutsianas
  29. Zhijian Yang
  30. Ranran Zhai
  31. Chenqing Zheng
  32. Graeme Grimes
  33. Rupert Beale
  34. Jonathan Millar
  35. Barbara Shih
  36. Sean Keating
  37. Marie Zechner
  38. Chris Haley
  39. David J. Porteous
  40. Caroline Hayward
  41. Jian Yang
  42. Julian Knight
  43. Charlotte Summers
  44. Manu Shankar-Hari
  45. Paul Klenerman
  46. Lance Turtle
  47. Antonia Ho
  48. Shona C. Moore
  49. Charles Hinds
  50. Peter Horby
  51. Alistair Nichol
  52. David Maslove
  53. Lowell Ling
  54. Danny McAuley
  55. Hugh Montgomery
  56. Timothy Walsh
  57. Alexandre C. Pereira
  58. Alessandra Renieri
  59. Xia Shen
  60. Chris P. Ponting
  61. Angie Fawkes
  62. Albert Tenesa
  63. Mark Caulfield
  64. Richard Scott
  65. Kathy Rowan
  66. Lee Murphy
  67. Peter J. M. Openshaw
  68. Malcolm G. Semple
  69. Andrew Law
  70. Veronique Vitart
  71. James F. Wilson
  72. J. Kenneth Baillie

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  1. ScreenIT

    SciScore for 10.1101/2020.09.24.20200048: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Both studies were approved by the appropriate research ethics committees (Scotland 15/SS/0110, England, Wales and Northern Ireland: 19/WM/0247).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The Arrays were imaged on an Illumina iScan platform and genotypes were called automatically using GenomeStudio Analysis software v2.0.3, GSAMD-24v3-0-EA_20034606_A1.bpm manifest and cluster file provided by manufacturer.
    GenomeStudio Analysis
    suggested: (OMICtools, RRID:SCR_002250)
    Variants were genotyped with the GATK GenotypeGVCFs tool v4.1.8.1,52 filtered to minimum depth 8X (95% sensitivity for heterozygous variant detection,53) merged and annotated with allele frequency with bcftools v1.10.2.
    GATK
    suggested: (GATK, RRID:SCR_001876)
    bcftools
    suggested: (SAMtools/BCFtools, RRID:SCR_005227)
    Tests for association between case-control status and allele dosage at individuals SNPs were performed by fitting logistic regression models using PLINK.
    PLINK
    suggested: (PLINK, RRID:SCR_001757)
    Controls: Replication: GenOMICC EUR loci were defined by clumping function of PLINK 1.9 and clumping parameters r2 0.1 pval=5e-8 and pval2 0.01, and distance to the nearest gene was calculated using ENSEMBL grch37 gene annotation.
    ENSEMBL
    suggested: (Ensembl, RRID:SCR_002344)

    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 10.1038/s41586-020-03065-y
  3. ScreenIT

    SciScore for 10.1101/2020.09.24.20200048: (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

    Experimental Models: Cell Lines
    SentencesResources
    SNPs with large weights in PC1, PC2 or PC3 were removed, keeping at least 2/3 of the number of pruned SNPs to keep as an input of the next round of King 2.1.
    PC2
    suggested: RRID:CVCL_0483)
    Experimental Models: Organisms/Strains
    SentencesResources
    SNP rs73064425 rs9380142 rs143334143 rs3131294 rs10735079 rs2109069 rs74956615 rs2236757 chr:pos (b37) 3:45901089 6:29798794 6:31121426 6:32180146 12:113380008 19:4719443 19:10427721 21:34624917 Risk T A A G A A A A Other beta gcc.
    SNP rs73064425 rs9380142 rs143334143 rs3131294 rs10735079 rs2109069 rs74956615 rs2236757 chr:pos
    suggested: None
    SNP rs67959919 rs143334143 rs9501257 rs622568 rs10087754 rs10860891 rs4766664
    SNP rs67959919 rs143334143 rs9501257 rs622568 rs10087754 rs10860891 rs4766664
    suggested: None
    Software and Algorithms
    SentencesResources
    Briefly, genetic ancestry was inferred for unrelated individuals passing quality control using ADMIXTURE and reference individuals from the 1000 Genomes project.
    ADMIXTURE
    suggested: (ADMIXTURE, RRID:SCR_001263)
    1000 Genomes
    suggested: (1000 Genomes Project and AWS, RRID:SCR_008801)
    The Arrays were imaged on an Illumina iScan platform and genotypes were called automatically using GenomeStudio Analysis software v2.0.3, GSAMD-24v3-0-EA_20034606_A1.bpm manifest and cluster file provided by manufacturer.
    GenomeStudio Analysis
    suggested: (OMICtools, RRID:SCR_002250)
    Variants were genotyped with the GATK GenotypeGVCFs tool v4.1.8.1,52 filtered to minimum depth 8X (95% sensitivity for heterozygous variant detection,53 ) merged and annotated with allele frequency with bcftools v1.10.2.
    bcftools
    suggested: (SAMtools/BCFtools, RRID:SCR_005227)
    Quality control Genotype calls were carefully examined within GenomeStudio using manufacturer and published54 recommendations, after excluding samples with low initial call rate (<90%) and reclustering the data thereafter.
    GenomeStudio
    suggested: (GenomeStudio, RRID:SCR_010973)
    Tests for association between case-control status and allele dosage at individuals SNPs were performed by fitting logistic regression models using PLINK.
    PLINK
    suggested: (PLINK, RRID:SCR_001757)
    Variants overlapping the positions of the imputed variants were called using GATk and variants with depth<8 (the minimum depth for which 95% coverage can be expected) were filtered.
    GATk
    suggested: (GATK, RRID:SCR_001876)
    Alternative allele frequency was calculated with PLINK 2.063 for both WGS and imputed data.
    WGS
    suggested: None
    Generation Scotland Generation Scotland: Scottish Family Health Study (hereafter referred to as Generation Scotland) is a population-based cohort of 24 084 participants sampled from five regional centers across Scotland(www.generationscotland.org).64 A large subset of participants were genotyped using either Illumina HumanOmniExpressExome-8v1_A or v1-2, and 20 032 passed QC criteria previously described.65,66 Genotype imputation using the TOPMed reference panel was recently performed (freeze 5b) using Minimac4 v1.0 on the University of Michigan serverhttps://imputationserver.sph.umich.edu.67 Imputation data from unrelated (genomic sharing identical by descent estimated using PLINK1.9 < 5%) participants were used as control genotypes in a GWAS using GenOMICC cases of European ancestry, for quality check purpose of associated variants.
    Minimac4
    suggested: None
    Replication GenOMICC EUR loci were defined by clumping function of PLINK 1.9 and clumping parameters r2 0.1 pval=5e-8 and pval2 0.01, and distance to the nearest gene was calculated using ENSEMBL grch37 gene annotation.
    ENSEMBL
    suggested: (Ensembl, RRID:SCR_002344)
    Post-GWAS analyses TWAS We performed transcriptome-wide association using the MetaXcan framework25 and the GTExv8 eQTL MASHR-M models available for download (http://predictdb.org/).
    MetaXcan
    suggested: None
    Analyses were conducted using Python 3.7.3 and SMR/HEIDI v1.03.
    Python
    suggested: (IPython, RRID:SCR_001658)
    SMR/HEIDI
    suggested: None
    Significant (as per GTEx v7; nominal p-value below nominal p-value threshold) local (distance to transcriptional start site < 1Mb) eQTL from GTEx v7 whole blood for protein coding genes (as per GENCODE v19) with a MAF > 0.01 (GTEx v7 and GenOMICC) were considered as potential instrumental variables.
    GENCODE
    suggested: (GENCODE, RRID:SCR_014966)
    Gene-level Gene-level burden of significance in the EUR ancestry group result was calculated using MAGMA v1.08.68 SNPs were annotated to genes by mapping based on genomic location.
    MAGMA
    suggested: (MAGMA, RRID:SCR_005757)
    The reference data files used to estimate LD are derived from Phase 3 of the 1000 Genomes Project.
    1000 Genomes Project
    suggested: (1000 Genomes Project and AWS, RRID:SCR_008801)
    68 Gene sets were queried from the databases KEGG 2019, Reactome 2016, GO Biological Process 2018, Biocarta 2016 and WikiPathways 2019.
    KEGG
    suggested: (KEGG, RRID:SCR_012773)
    GO Biological
    suggested: None
    WikiPathways
    suggested: (WikiPathways, RRID:SCR_002134)

    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.

    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.

  4. Version published to 10.1101/2020.09.24.20200048v1 on medRxiv
  5. Version published to 10.1101/2020.09.24.20200048v2 on medRxiv