Genome-wide association study between SARS-CoV-2 single nucleotide polymorphisms and virus copies during infections

Ke Li,Chrispin Chaguza, Yi Ting Chew,Nicholas F.G. Chen,David Ferguson, Sameer Pandya, Nick Kerantzas,Wade Schulz, Yale SARS-CoV- Genomic Surveillance Initiative,Anne M. Hahn,Virginia E. Pitzer,Daniel M. Weinberger,Nathan D. Grubaugh

medrxiv(2024)

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摘要
Variations in viral loads generated during SARS-CoV-2 infections can influence COVID-19 disease progression and the likelihood of onward transmission. However, the host and virus factors that may impact viral loads and infection dynamics are not fully understood. Here, we conducted virus whole genome sequencing and measured viral copies using RT-qPCR from 9,902 SARS-CoV-2 infections over a 2-year period to examine the relative impact of host factors and virus genetic variation on changes in viral copies. We first used statistical regression models to show that host age and SARS-CoV-2 variant significantly impact viral copies, but vaccination status does not. Then, using a genome-wide association study (GWAS) approach, we identified multiple nucleotide substitutions corresponding to amino acid changes in the SARS-CoV-2 genome associated with variations in viral copies. In particular, we analyzed the temporal patterns and found that SNPs associated with higher viral copies were predominantly observed in Omicron BA.2/BA.4/BA.5/XBB infections, whereas those associated with decreased viral copies were mostly observed in infections with Delta and Omicron BA.1 variants. Our work showcases how GWAS can be a useful tool for probing phenotypes related to SNPs in viral genomes, which can be used to characterize emerging variants and monitor therapeutic interventions. ### Competing Interest Statement NDG is a paid consultant for BioNTech, DMW has received consulting fees from Pfizer, Merck, and GSK, unrelated to this manuscript, and has been PI on research grants from Pfizer and Merck to Yale, unrelated to this manuscript. ### Funding Statement This project is supported by the Centers for Disease Control and Prevention (CDC) Broad Agency Announcement Contract 75D30122C14697 (NDG). This work does not necessarily represent the views of the CDC. ### 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: The Institutional Review Board from the Yale University Human Research Protection Program determined that the RT-qPCR testing and sequencing of de-identified remnant COVID-19 clinical samples obtained from clinical partners conducted in this study is not research involving human subjects (IRB Protocol ID: 2000028599). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. 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, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data and code used in this study are publicly available on Github: https://github.com/grubaughlab/2024\_paper\_GWAS. All genome sequences used for the GWAS analysis and a subset of the associated metadata (accession number, virus name, collection date, originating lab and submitting lab, and the list of authors) in this dataset are published in GISAIDs EpiCoV database: https://doi.org/10.55876/gis8.240219fh. The de-identified and coded clinical metadata associated with the sequenced samples are available upon request with IRB approval.
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