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SARS-CoV-2 genomic variations associated with mortality rate of COVID-19.

ABSTRACT: The coronavirus disease 2019 (COVID-19) outbreak, caused by SARS-CoV-2, has rapidly expanded to a global pandemic. However, numbers of infected cases, deaths, and mortality rates related to COVID-19 vary from country to country. Although many studies were conducted, the reasons of these differences have not been clarified. In this study, we comprehensively investigated 12,343 SARS-CoV-2 genome sequences isolated from patients/individuals in six geographic areas and identified a total of 1234 mutations by comparing with the reference SARS-CoV-2 sequence. Through a hierarchical clustering based on the mutant frequencies, we classified the 28 countries into three clusters showing different fatality rates of COVID-19. In correlation analyses, we identified that ORF1ab 4715L and S protein 614G variants, which are in a strong linkage disequilibrium, showed significant positive correlations with fatality rates (r = 0.41, P = 0.029 and r = 0.43, P = 0.022, respectively). We found that BCG-vaccination status significantly associated with the fatality rates as well as number of infected cases. In BCG-vaccinated countries, the frequency of the S 614G variant had a trend of association with the higher fatality rate. We also found that the frequency of several HLA alleles, including HLA-A*11:01, were significantly associated with the fatality rates, although these factors were associated with number of infected cases and not an independent factor to affect fatality rate in each country. Our findings suggest that SARS-CoV-2 mutations as well as BCG-vaccination status and a host genetic factor, HLA genotypes might affect the susceptibility to SARS-CoV-2 infection or severity of COVID-19.

SUBMITTER: Toyoshima Y

PROVIDER: S-EPMC7375454 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background The novel coronavirus disease (COVID-19) has claimed lots of lives, posing a dire threat to global health. It was predicted that the coronavirus outbreak in the African population would be very lethal and result to economic devastation owing to the prevalence of immune-compromised population, poverty, low lifespan, fragile health care systems, poor economy, and lifestyle factors. Accumulation of mutations gives virus selective advantage for host invasion and adaptation, higher transmissibility of more virulent strains, and drug resistance. The present study determined the severe acute respiratory syndrome-2 (SARS-CoV-2) genomic variability and the contributory factors to the low COVID-19 fatality in Africa. To assess the SARS-CoV-2 mutational landscape, 924 viral sequences from the Africa region with their sociobiological characteristics mined from the Global Initiative on Sharing All Influenza Data (GISAID) database were analyzed. Results Mutational analysis of the SARS-CoV-2 sequences revealed highly recurrent mutations in the SARS-CoV-2 spike glycoprotein D614G (97.2%), concurrent R203K, and G204R (65.2%) in the nucleocapsid phosphoprotein, and P4715L (97.2%) in the RNA-dependent RNA polymerase flagging these regions as SARS-CoV-2 mutational hotspots in the African population. COVID-19 is more severe in older people (> 65?years); Africa has a low percentage of people within this age group (4.36%). The average age of the infected patients observed in this study is 46?years with only 47 infected patients (5.1%) above 65?years in Africa in comparison to 13.12% in countries in other continents with the highest prevalence of COVID-19. Conclusions Africa’s young generation, the late incidence of the disease, and adherence to public health guidelines are important indicators that may have contributed to the observed low COVID-19 deaths in Africa. However, with the easing of lockdown and regulatory policies, daily increasing incidence in most countries, and low testing and sequencing rate, the epidemiology and the true impact of the pandemic in Africa remain to be unraveled.

Project description:The COVID-19 epidemic of 2019-20 is due to the novel coronavirus SARS-CoV-2. Following first case description in December, 2019 this virus has infected over 10 million individuals and resulted in at least 500,000 deaths world-wide. The virus is undergoing rapid mutation, with two major clades of sequence variants emerging. This study sought to determine whether SARS-CoV-2 sequence variants are associated with differing outcomes among COVID-19 patients in a single medical system. Whole genome SARS-CoV-2 RNA sequence was obtained from isolates collected from patients registered in the University of Washington Medicine health system between March 1 and April 15, 2020. Demographic and baseline clinical characteristics of patients and their outcome data including their hospitalization and death were collected. Statistical and machine learning models were applied to determine if viral genetic variants were associated with specific outcomes of hospitalization or death. Full length SARS-CoV-2 sequence was obtained 190 subjects with clinical outcome data. 35 (18.4%) were hospitalized and 14 (7.4%) died from complications of infection. A total of 289 single nucleotide variants were identified. Clustering methods demonstrated two major viral clades, which could be readily distinguished by 12 polymorphisms in 5 genes. A trend toward higher rates of hospitalization of patients with Clade 2 infections was observed (p?=?0.06, Fisher's exact). Machine learning models utilizing patient demographics and co-morbidities achieved area-under-the-curve (AUC) values of 0.93 for predicting hospitalization. Addition of viral clade or sequence information did not significantly improve models for outcome prediction. In summary, SARS-CoV-2 shows substantial sequence diversity in a community-based sample. Two dominant clades of virus are in circulation. Among patients sufficiently ill to warrant testing for virus, no significant difference in outcomes of hospitalization or death could be discerned between clades in this sample. Major risk factors for hospitalization and death for either major clade of virus include patient age and comorbid conditions.

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SARS-CoV-2 genomic variations associated with mortality rate of COVID-19.

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