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a recent paper predicts outcomes from mutations
Different mutations in SARS-CoV-2 associate with severe nd mild outcome
Different mutations in SARS-CoV-2 associate with severe nd mild outcome
Introduction Genomic alterations in a viral genome can lead to either better or worse outcome and identifying these mutations is of utmost importance. Here, we correlated protein-level mutations in the SARS-CoV-2 virus to clinical outcome.
Methods Mutations in viral sequences from the GISAID virus repository were evaluated by using “hCoV-19/Wuhan/WIV04/2019” as the reference. Patient outcomes were classified as mild disease, hospitalization and severe disease (death or documented treatment in an intensive-care unit). Chi-square test was applied to examine the association between each mutation and patient outcome. False discovery rate was computed to correct for multiple hypothesis testing and results passing a FDR cutoff of 5% were accepted as significant.
Result Mutations were mapped to amino acid changes for 2,120 non-silent mutations. Mutations correlated to mild outcome were located in the ORF8, NSP6, ORF3a, NSP4, and in the nucleocapsid phosphoprotein N. Mutations associated with inferior outcome were located in the surface (S) glycoprotein, in the RNA dependent RNA polymerase, in the 3’-to5’ exonuclease, in ORF3a, NSP2 and N. Mutations leading to severe outcome with low prevalence were found in the surface (S) glycoprotein and in NSP7. Five out of 17 of the most significant mutations mapped onto a 10 amino acid long phosphorylated stretch of N indicating that in spite of obvious sampling restrictions the approach can find functionally relevant sites in the viral genome.
Conclusions We demonstrate that mutations in the viral genes may have a direct correlation to clinical outcome. Our results help to quickly identify SARS-CoV-2 infections harboring mutations related to severe outcome.
### Competing Interest Statement
The authors have declared no competing interest.
### Funding Statement
The research was financed by the 2018-2.1.17-TET-KR-00001 and KH-129581 grants and by the Higher Education Institutional Excellence Programme of the Ministry for Innovation and Technology (MIT) in Hungary, within the framework of the Bionic thematic programme of the Semmelweis University as well as by OTKA grant 12065 provided by MIT, Hungary to Pazmany University. The authors wish to acknowledge the support of ELIXIR Hungary (www.elixir-hungary.org) as well as the advice of Drs Sebastian Maurer-Stroh (Bioinformatics Institute, A*STAR, Singapore) and Balazs Ligeti (Pazmany University, Budapest).
### Author Declarations
I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
Yes
The details of the IRB/oversight body that provided approval or exemption for the research described are given below:
In this study the authors used publicly available data.
All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.
Yes
I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).
Yes
I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.
Yes
All available SARS-CoV-2 (taxid: 2697049) viral nucleic acid sequences were downloaded from the GISAID virus repository (https://www.gisaid.org/). The mutations were evaluated using the CoVsurver (https://corona.bii.a-star.edu.sg).
<https://www.gisaid.org/>
<https://corona.bii.a-star.edu.sg>
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