| Autor: |
Lue Ping Zhao, Pavitra Roychoudhury, Keith Jerome, Peter Gilbert, Joshua Schiffer, Terry Lybrand, Thomas Payne, April K Randhawa, Sara E Thiebaud, Margaret Mills, Alexander Greninger, Chul-Woo Pyo, Ruihan Wang, Renyu Li, Alexander S Thomas, Brandon M Norris, Wyatt C Nelson, Daniel Geraghty |
| Rok vydání: |
2021 |
| DOI: |
10.21203/rs.3.rs-888049/v2 |
| Popis: |
SARS-CoV-2 is spreading worldwide with continuously evolving variants, some of which occur in the Spike protein and appear to increase the viral transmissibility. However, variants that cause severe COVID-19 or lead to other breakthroughs have not been well characterized. To discover such viral variants, we assembled a cohort of 683 COVID-19 patients; 388 inpatients (“cases”) and 295 outpatients (“controls”) from April to August 2020 using electronically captured COVID test request forms and sequenced their viral genomes. To improve the analytic power, we accessed 7,137 viral sequences in Washington State to filter out viral single nucleotide variants (SNVs) that did not have significant expansions over the collection period. Applying this filter led to the identification of 53 SNVs that were statistically significant, of which 13 SNVs each had 3 or more variant copies in the discovery cohort. Correlating these selected SNVs with case/control status, eight SNVs were found to significantly associate with inpatient status (q-values−11) that appeared in April 2020, peaked in June, and persisted into January 2021. This association was replicated (OR=5.46, p-value=4.71*10−12) in an independent cohort of 964 COVID-19 patients (June 1, 2020 to March 31, 2021). The haplotype included a synonymous change N73N in endoRNase, and three non-synonymous changes coding residues R203K, R203S and G204R in the nucleocapsid protein. This discovery points to the potential functional role of the nucleocapsid protein in triggering “cytokine storms” and severe COVID-19 that led to hospitalization. The study further emphasizes a need for tracking and analyzing viral sequences in correlations with clinical status. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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