Author:
Majchrzak Michał,Madej Łukasz,Łysek-Gładysińska Małgorzata,Zarębska-Michaluk Dorota,Zegadło Katarzyna,Dziuba Anna,Nogal-Nowak Katarzyna,Kondziołka Wioleta,Sufin Iwona,Myszona-Tarnowska Mieczysława,Jaśkowski Mateusz,Kędzierski Mateusz,Maciukajć Jadwiga,Matykiewicz Jarosław,Głuszek Stanisław,Adamus-Białek Wioletta
Abstract
Abstract
Background
The evolution of SARS-CoV-2 has been observed from the very beginning of the fight against COVID-19, some mutations are indicators of potentially dangerous variants of the virus. However, there is no clear association between the genetic variants of SARS-CoV-2 and the severity of COVID-19. We aimed to analyze the genetic variability of RdRp in correlation with different courses of COVID-19.
Results
The prospective study included 77 samples of SARS-CoV-2 isolated from outpatients (1st degree of severity) and hospitalized patients (2nd, 3rd and 4th degree of severity). The retrospective analyses included 15,898,266 cases of SARS-CoV-2 genome sequences deposited in the GISAID repository. Single-nucleotide variants were identified based on the four sequenced amplified fragments of SARS-CoV-2. The analysis of the results was performed using appropriate statistical methods, with p < 0.05, considered statistically significant. Additionally, logistic regression analysis was performed to predict the strongest determinants of the observed relationships. The number of mutations was positively correlated with the severity of the COVID-19, and older male patients. We detected four mutations that significantly increased the risk of hospitalization of COVID-19 patients (14676C > T, 14697C > T, 15096 T > C, and 15279C > T), while the 15240C > T mutation was common among strains isolated from outpatients. The selected mutations were searched worldwide in the GISAID database, their presence was correlated with the severity of COVID-19.
Conclusion
Identified mutations have the potential to be used to assess the increased risk of hospitalization in COVID-19 positive patients. Experimental studies and extensive epidemiological data are needed to investigate the association between individual mutations and the severity of COVID-19.
Publisher
Springer Science and Business Media LLC