SARS-CoV-2 Mutations and COVID-19 Clinical Outcome: Mutation Global Frequency Dynamics and Structural Modulation Hold the Key

Genetic features of SARS-CoV-2 Alpha, Delta, and Omicron variants and their association with the clinical severity of COVID-19 in Vietnam

Objectives

We investigated the genetic variations in the Alpha, Delta, and Omicron variants of SARS-CoV-2 and their association with clinical status and treatment outcomes in patients with COVID-19.

Methods

MiSeq was used to sequence the Alpha, Delta, and Omicron genomes, and MEGA 6.6 was used to define the nucleotide variations. We determined the association between clinical severity and treatment outcomes for the SARS-CoV-2 variants.

Results

The BA.1.1 and BA.2 lineages of the Omicron variant had 57-59 mutations, which is 2-2.7-fold higher than that of the B.1.1.7 (Alpha), B.1.617.2, and AY.57 (Delta) lineages. We found distinct mutations in SARS-CoV-2: five in Alpha (C26305T, G26558T, G7042T, C14120T, and C27509T); seven in Delta (C26408T, C1403T, C5184T, C9891T, T11418C, C11514T, and C22227T); and three in Omicron (C26408T, C8991T, and C25810T). Patients with the Delta variant had a severe rate of 23.8%, a critical rate of 53.7%, and a mortality rate of 38.9%, which were significantly higher than those with the Omicron and Alpha variants.

Conclusions

The Alpha, Delta, and Omicron variants in this study had genetic diversity and differed from the strains reported in other countries, with the Delta variant producing significantly more clinical severity and mortality than the Alpha and Omicron variants.

Unravelling the link between SARS-CoV-2 mutation frequencies, patient comorbidities, and structural dynamics

Genomic surveillance is crucial for tracking emergence and spread of novel variants of pathogens, such as SARS-CoV-2, to inform public health interventions and to enforce control measures. However, in some settings especially in low- and middle- income counties, where sequencing platforms are limited, only certain patients get to be selected for sequencing surveillance. Here, we show that patients with multiple comorbidities potentially harbour SARS-CoV-2 with higher mutation rates and thus deserve more attention for genomic surveillance. The relationship between the patient comorbidities, and type of amino acid mutations was assessed. Correlation analysis showed that there was a significant tendency for mutations to occur within the ORF1a region for patients with higher number of comorbidities. Frequency analysis of the amino acid substitution within ORF1a showed that nsp3 P822L of the PLpro protease was one of the highest occurring mutations. Using molecular dynamics, we simulated that the P822L mutation in PLpro represents a system with lower Root Mean Square Deviation (RMSD) fluctuations, and consistent Radius of gyration (Rg), Solvent Accessible Surface Area (SASA) values-indicate a much stabler protein than the wildtype. The outcome of this study will help determine the relationship between the clinical status of a patient and the mutations of the infecting SARS-CoV-2 virus.

The RdRp genotyping of SARS-CoV-2 isolated from patients with different clinical spectrum of COVID-19

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.

Epidemiology and analysis of SARS-CoV-2 Omicron subvariants BA.1 and 2 in Taiwan

The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first detected in October 2021, possessed many mutations compared to previous variants. We aimed to identify and analyze SARS-CoV-2 Omicron subvariants among coronavirus disease 2019 (COVID-19) patients between January 2022 and September 2022 in Taiwan. The results revealed that BA.2.3.7, featuring K97E and G1251V in the spike protein compared with BA.2, emerged in March 2022 and persistently dominated between April 2022 and August 2022, resulting in the largest COVID-19 outbreak since 2020. The accumulation of amino acid (AA) variations, mainly AA substitution, in the spike protein was accompanied by increasing severity in Omicron-related COVID-19 between April 2022 and January 2023. Older patients were more likely to have severe COVID-19, and comorbidity was a risk factor for COVID-19-related mortality. The accumulated case fatality rate (CFR) dropped drastically after Omicron variants, mainly BA.2.3.7, entered Taiwan after April 2022, and the CFR was 0.16% in Taiwan, which was lower than that worldwide (0.31%) between April 2021 and January 2023. The relatively low CFR in Omicron-related COVID-19 patients can be attributed to adjustments to public health policies, promotion of vaccination programs, effective antiviral drugs, and the lower severity of the Omicron variant.

Identification of critical SARS-CoV-2 amino acids associated with COVID-19 hospitalization rate using machine learning and statistical modeling: An observational study in the United States

BACKGROUND

The COVID-19 pandemic has put many medical systems on the verge of collapse in the last two years. Virus mutation was one of the important factors affecting the COVID-19 infection severity and hospitalizations. Although over ten thousand SARS-CoV-2 mutations being reported since the beginning of the COVID-19 pandemic, only a small percentage of mutations are likely to affect the virus phenotype and change its severity. Finding out which amino acids have the greatest impact on COVID-19 hospitalization rate is an important research question.

METHODS

This observational study used the COVID-19 case hospitalization ratio (CHR) to represent the virus severity related with hospitalization. The database is based on the daily state-level epidemiological and genomic sequential data in the United States from the Alpha wave to the first Omicron wave. The critical amino acids that mostly affected the CHR were determined by using four types of models including extreme gradient boosting decision trees (XGBoost), artificial neural networks (ANNs), logistic regression and Lasso regression models.

RESULTS

The XGBoost, ANN, logistic regression, and Lasso regression models all produce excellent results (mean square error for all state-level models does not exceed 0.0008 using the testing dataset). Based on the rank of importance of all covariates, the critical amino acids most affecting the CHR were identified, including T19, L24, P25, P26, A27, A67, H69, V70, T95, G142, V143, Y145, E156, F157, N211, L212, V213, R214, D215, G339, R346, S373, L452, S477, T478, E484, N501, A570, P681, and T716.

CONCLUSION

This study identified critical amino acids that are most likely to affect the hospitalization rate, allowing public health workers to monitor these highly risky amino acids and raise an alarm immediately when more severe mutations occur. Furthermore, the methodology and results may be extended to other regions.

Nsp3-N interactions are critical for SARS-CoV-2 fitness and virulence

SARS-CoV-2, the causative agent of COVID-19 encodes at least 16 nonstructural proteins of variably understood function. Nsp3, the largest nonstructural protein contains several domains, including a SARS-unique domain (SUD), which occurs only in Sarbecovirus. The SUD has a role in preferentially enhancing viral translation. During isolation of mouse-adapted SARS-CoV-2, we isolated an attenuated virus that contained a single mutation in a linker region of nsp3 (nsp3-S676T). The S676T mutation decreased virus replication in cultured cells and primary human cells and in mice. Nsp3-S676T alleviated the SUD translational enhancing ability by decreasing the interaction between two translation factors, Paip1 and PABP1. We also identified a compensatory mutation in the nucleocapsid (N) protein (N-S194L) that restored the virulent phenotype, without directly binding to SUD. Together, these results reveal an aspect of nsp3-N interactions, which impact both SARS-CoV-2 replication and, consequently, pathogenesis.

Comparative assessment of SARS CoV2-associated mortalities in 3 COVID waves and related risk factors: The South Kashmir's experience

Introduction

Severe acute respiratory syndrome coronavirus 2 causing coronavirus disease 2019 (COVID-19) pandemic have spurted in three major waves in India at different times and had different levels of severity in different waves. The objective of our study was to determine the comparative mortality rate in three COVID-19 waves and determine the factors associated with mortality.

Methods

We identified a cohort of 1,132 COVID-19 patients who were admitted between April 14, 2020 and February 08, 2022 at our center. All the admitted patients with positive COVID-polymerase chain reaction were included in the study. Sample characteristics were determined by screening age, sex, socio-economic status, occupation, symptomatology of COVID, patient status on admission, baseline investigations, comorbidities, medical history, oxygen dosage needed during admission, the span of hospital stay, diagnosis, and vitals such as blood pressure, pulse, and oxygen saturation. All the data were procured from an institutional database.

Results

In total, 1,132 patients included in the study, the mean age was 65.08 ± 12.29 and 56% were males. The affliction rate was 42.13% in >60 years, 29.5% in 46-60 years, 20.8% in 31-45 years, and 7.4% in 30 years' group. In the first, second, and third waves of COVID-19, the mortality rates were 13.21%, 23.53%, and 11.39%, respectively. Among the comorbidities, mortality rates were proportionately higher in those with hypertension (6.7%), and diabetes (5.5%), than those with chronic obstructive pulmonary disease (3.3%), chronic kidney disease (CKD) (1.5%), heart disease (1.6%), and malignancy (0.2%).

Conclusion

We identify the peaked mortalities in the second encounter which was predicted by age, comorbidities such as hypertension, and diabetes.

Molnupiravir: A Versatile Prodrug against SARS-CoV-2 Variants

The nucleoside analog β-D-N4-hydroxycytidine is the active metabolite of the prodrug molnupiravir and is accepted as an efficient drug against COVID-19. Molnupiravir targets the RNA-dependent RNA polymerase (RdRp) enzyme, which is responsible for replicating the viral genome during the replication process of certain types of viruses. It works by disrupting the normal function of the RdRp enzyme, causing it to make mistakes during the replication of the viral genome. These mistakes can prevent the viral RNA from being transcribed, converted into a complementary DNA template, translated, or converted into a functional protein. By disrupting these crucial steps in the viral replication process, molnupiravir can effectively inhibit the replication of the virus and reduce its ability to cause disease. This review article sheds light on the impact of molnupiravir and its metabolite on SARS-CoV-2 variants of concern, such as delta, omicron, and hybrid/recombinant variants. The detailed mechanism and molecular interactions using molecular docking and dynamics have also been covered. The safety and tolerability of molnupiravir in patients with comorbidities have also been emphasized.

Prevalence of symptoms, comorbidities, and reinfections in individuals infected with Wild-Type SARS-CoV-2, Delta, or Omicron variants: a comparative study in western Mexico

Introduction

The variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been classified into variants of interest (VOIs) or concern (VOCs) to prioritize global monitoring and research on variants with potential risks to public health. The SARS-CoV-2 high-rate mutation can directly impact the clinical disease progression, epidemiological behavior, immune evasion, vaccine efficacy, and transmission rates. Therefore, epidemiological surveillance is crucial for controlling the COVID-19 pandemic. In the present study, we aimed to describe the prevalence of wild-type (WT) SARS-CoV-2 and Delta and Omicron variants in Jalisco State, Mexico, from 2021 to 2022, and evaluate the possible association of these variants with clinical manifestations of COVID-19.

Methods

Four thousand and ninety-eight patients diagnosed with COVID-19 by real-time PCR (COVIFLU, Genes2Life, Mexico) from nasopharyngeal samples from January 2021 to January 2022 were included. Variant identification was performed by the RT-qPCR Master Mut Kit (Genes2Life, Mexico). A study population follow-up was performed to identify patients who had experienced reinfection after being vaccinated.

Results and Discussion

Samples were grouped into variants according to the identified mutations: 46.3% were Omicron, 27.9% were Delta, and 25.8% were WT. The proportions of dry cough, fatigue, headache, muscle pain, conjunctivitis, fast breathing, diarrhea, anosmia, and dysgeusia were significantly different among the abovementioned groups (p < 0.001). Anosmia and dysgeusia were mainly found in WT-infected patients, while rhinorrhea and sore throat were more prevalent in patients infected with the Omicron variant. For the reinfection follow-up, 836 patients answered, from which 85 cases of reinfection were identified (9.6%); Omicron was the VOC that caused all reported reinfection cases. In this study, we demonstrate that the Omicron variant caused the biggest outbreak in Jalisco during the pandemic from late December 2021 to mid-February 2022 but with a less severe form than the one demonstrated by Delta and WT. The co-analysis of mutations and clinical outcomes is a public health strategy with the potential to infer mutations or variants that could increase disease severity and even be an indicator of long-term sequelae of COVID-19.

COVID-19 Clinical Features and Outcomes in Elderly Patients during Six Pandemic Waves

Many elderly patients with severe SARS-CoV-2 infections and COVID-19 infections are admitted to intensive care units. Age was previously identified as an independent risk factor for death and contributed to the greater severity of COVID-19. The elderly may have diminished lung functions, poor reactions to artificial ventilation, and compromised immune systems. However, it is yet uncertain how each pandemic wave and the predominant SARS-CoV-2 strains contribute to varying results and how patient groups such as the elderly are impacted. Comparing six COVID-19 pandemic waves, the objective of this study was to examine the variation in case severity, symptomatology, ICU hospitalizations, and mortality among SARS-CoV-2-infected elderly individuals. The study followed a retrospective design, including 60 eligible patients older than 70 years in each of the six pandemic wave groups, after matching them by the number of comorbidities and gender. SARS-CoV-2 infection during the first, third, and fourth pandemic waves had a significantly higher risk of mortality for hospitalized patients. Confusion and dyspnea at admission were significant risk factors for ICU admission in elderly patients (β = 1.92, respectively β = 3.65). The laboratory parameters identified decreased lymphocytes (β = 2.11), elevated IL-6 (β = 1.96), and procalcitonin (β = 2.46) as the most significant risk factors. The third and fourth COVID-19 waves had considerably more severe infections (31.7% and 26.7%) than the sixth wave (13.3%). Median ICU stay and percentage of patients receiving oxygen support also differed across pandemic waves. However, mortality rates between the six pandemic waves were similar. The average length of hospitalization varied dramatically among the six pandemic waves. Although senior patients are more likely to have worse COVID-19 outcomes after hospitalization, this risk is mitigated by the greater prevalence of comorbidities and frailty among the elderly. The six pandemic waves that were specifically evaluated did not reveal considerably disproportionate variations in terms of patient mortality; however, during the fourth pandemic wave, there were likely more hospitalized patients with severe COVID-19 in Romania. It is probable that certain circulating SARS-CoV-2 strains were more infectious, resulting in an increase in infections and a strain on healthcare systems, which might explain the variations found in our research.

Genome Similarities between Human-Derived and Mink-Derived SARS-CoV-2 Make Mink a Potential Reservoir of the Virus

SARS-CoV-2 has RNA as the genome, which makes the virus more prone to mutations. Occasionally, mutations help a virus to cross the species barrier. SARS-CoV-2 infections in humans and minks (Neovison vison) are examples of zoonotic spillover. Many studies on the mutational analysis of human-derived SARS-CoV-2 have been published, but insight into the mink-derived SARS-CoV-2 genome of mutations is still required. Here, we performed a mutation analysis of the mink-derived SARS-CoV-2 genome sequences. We analyzed all available full-length mink-derived SARS-CoV-2 genome sequences on GISAID (214 genome sequences from the Netherlands and 133 genome sequences from Denmark). We found a striking resemblance between human-derived and mink-derived SARS-CoV-2. Our study showed that mutation patterns in the SARS-CoV-2 genome samples from the Netherlands and Denmark were different. Out of the 201 mutations we found, only 13 mutations were shared by the Netherlands' and Denmark's mink-derived samples. We found that six mutations were prevalent in the mink-derived SARS-CoV-2 genomes, and these six mutations are also known to be prevalent in human-derived SARS-CoV-2 variants. Our study reveals that the G27948T mutation in SARS-CoV-2 leads to truncation of ORF8, which was also reported in human-derived SARS-CoV-2, thus indicating that the virus can replicate without the full-length ORF8. These resemblances between mink-derived and human-derived SARS-CoV-2 enable the virus to cross the species barrier and suggest mink a potential reservoir for the virus.

Phylogenetic analysis and comparative genomics of SARS-CoV-2 from survivor and non-survivor COVID-19 patients in Cordoba, Argentina

BACKGROUND

The SARS-CoV-2 virus is responsible for the COVID-19 pandemic. To better understand the evolution of SARS-CoV-2 early in the pandemic in the Province of Cordoba, Argentina, we performed a comparative genomic analysis of SARS-CoV-2 strains detected in survivors and non-survivors of COVID-19. We also carried out an epidemiological study to find a possible association between the symptoms and comorbidities of these patients with their clinical outcomes.

RESULTS

A representative sampling was performed in different cities in the Province of Cordoba. Ten and nine complete SARS-CoV-2 genomes were obtained by next-generation sequencing of nasopharyngeal specimens from non-survivors and survivors, respectively. Phylogenetic and phylodynamic analyses revealed multiple introductions of the most common lineages in South America, including B.1, B.1.1.1, B.1.499, and N.3. Fifty-six mutations were identified, with 14% of those in common between the non-survivor and survivor groups. Specific SARS-CoV-2 mutations for survivors constituted 25% whereas for non-survivors they were 41% of the repertoire, indicating partial selectivity. The non-survivors' variants showed higher diversity in 9 genes, with a majority in Nsp3, while the survivors' variants were detected in 5 genes, with a higher incidence in the Spike protein. At least one comorbidity was present in 60% of non-survivor patients and 33% of survivors. Age 75-85 years (p = 0.018) and hospitalization (p = 0.019) were associated with non-survivor patients. Related to the most common symptoms, the prevalence of fever was similar in both groups, while dyspnea was more frequent among non-survivors and cough among survivors.

CONCLUSIONS

This study describes the association of clinical characteristics with the clinical outcomes of survivors and non-survivors of COVID-19 patients, and the specific mutations found in the genome sequences of SARS-CoV-2 in each patient group. Future research on the functional characterization of novel mutations should be performed to understand the role of these variations in SARS-CoV-2 pathogenesis and COVID-19 disease outcomes. These results add new genomic data to better understand the evolution of the SARS-CoV-2 variants that spread in Argentina during the first wave of the COVID-19 pandemic.