Meta-Analysis and Structural Dynamics of the Emergence of Genetic Variants of SARS-CoV-2

Castonguay, Nicolas; Zhang, Wandong; Langlois, Marc‐André

doi:10.3389/fmicb.2021.676314

Cited by 19 publications

(18 citation statements)

References 53 publications

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“…All of these mutations are now seen predominantly in VOC 20I Alpha. The mutations C3267T (T1001I) ( Public Health England, 2021 ; Castonguay et al., 2021 ; Srivastava et al., 2021 ), A28111G (Y73C) ( Public Health England, 2021 , C23271A (A570D) ( Public Health England, 2021 ), C913T (S216S) ( Castonguay et al., 2021 ), T28282A (D3E) ( He et al., 2021 ), G28280C (D3H) ( Castonguay et al., 2021 ; He et al., 2021 ), and A28281T (D3V) ( Castonguay et al., 2021 ) are reported in 20I Alpha clade. Of these, C15279T (H5005H) is a clade-defining mutation for 20I ( Hadfield et al., 2018 ).…”

Section: Discussionmentioning

confidence: 99%

Learning From Biological and Computational Machines: Importance of SARS-CoV-2 Genomic Surveillance, Mutations and Risk Stratification

Bhat

Pandey

Kanakan

et al. 2021

Front. Cell. Infect. Microbiol.

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The global coronavirus disease 2019 (COVID-19) pandemic has demonstrated the range of disease severity and pathogen genomic diversity emanating from a singular virus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2). This diversity in disease manifestations and genomic mutations has challenged healthcare management and resource allocation during the pandemic, especially for countries such as India with a bigger population base. Here, we undertake a combinatorial approach toward scrutinizing the diagnostic and genomic diversity to extract meaningful information from the chaos of COVID-19 in the Indian context. Using methods of statistical correlation, machine learning (ML), and genomic sequencing on a clinically comprehensive patient dataset with corresponding with/without respiratory support samples, we highlight specific significant diagnostic parameters and ML models for assessing the risk of developing severe COVID-19. This information is further contextualized in the backdrop of SARS-CoV-2 genomic features in the cohort for pathogen genomic evolution monitoring. Analysis of the patient demographic features and symptoms revealed that age, breathlessness, and cough were significantly associated with severe disease; at the same time, we found no severe patient reporting absence of physical symptoms. Observing the trends in biochemical/biophysical diagnostic parameters, we noted that the respiratory rate, total leukocyte count (TLC), blood urea levels, and C-reactive protein (CRP) levels were directly correlated with the probability of developing severe disease. Out of five different ML algorithms tested to predict patient severity, the multi-layer perceptron-based model performed the best, with a receiver operating characteristic (ROC) score of 0.96 and an F1 score of 0.791. The SARS-CoV-2 genomic analysis highlighted a set of mutations with global frequency flips and future inculcation into variants of concern (VOCs) and variants of interest (VOIs), which can be further monitored and annotated for functional significance. In summary, our findings highlight the importance of SARS-CoV-2 genomic surveillance and statistical analysis of clinical data to develop a risk assessment ML model.

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Section: Discussionmentioning

confidence: 99%

Learning From Biological and Computational Machines: Importance of SARS-CoV-2 Genomic Surveillance, Mutations and Risk Stratification

Bhat

Pandey

Kanakan

et al. 2021

Front. Cell. Infect. Microbiol.

View full text Add to dashboard Cite

show abstract

“…Similarly, the effect of new variant strains on transmissibility and other disease parameters is of particular concern. For example, variants B.1.1.7, B.1.351, and P.1 have demonstrated an impact on transmissibility, inactivity, and antibody escape capabilities [ 7 ].…”

Section: Methodsmentioning

confidence: 99%

“…One year into the pandemic, many factors and constraints are still unknown and outside of the control of policymakers, including the behavioral response to vaccination (i.e., change in population mixing behaviors after vaccination), vaccine uptake or vaccine efficacy to prevent transmission [ 6 ]. Variant strains with higher transmissibility [ 7 ] might also hamper the effects of social distancing measures and could impact vaccine efficacy, making it difficult to define and commit to a defined long-term strategy.…”

Section: Introductionmentioning

confidence: 99%

Reopening California: Seeking robust, non-dominated COVID-19 exit strategies

et al. 2021

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The COVID-19 pandemic required significant public health interventions from local governments. Although nonpharmaceutical interventions often were implemented as decision rules, few studies evaluated the robustness of those reopening plans under a wide range of uncertainties. This paper uses the Robust Decision Making approach to stress-test 78 alternative reopening strategies, using California as an example. This study uniquely considers a wide range of uncertainties and demonstrates that seemingly sensible reopening plans can lead to both unnecessary COVID-19 deaths and days of interventions. We find that plans using fixed COVID-19 case thresholds might be less effective than strategies with time-varying reopening thresholds. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower. The approach used in this paper could also prove useful for other public health policy problems in which policymakers need to make robust decisions in the face of deep uncertainty.

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“…The human "coronavirus disease 2019" (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is associated with high morbidity and mortality [1][2][3][4][5][6]. It has generated a worldwide pandemic, the evolution of which is still uncertain due to the emergence of variants [7][8][9][10][11]. Hospitals worldwide have been facing the increasing demand of patients requiring oxygen supply, ventilators, and intensive care.…”

Section: Introductionmentioning

confidence: 99%

SARS-CoV-2 induces human endogenous retrovirus type W envelope protein expression in blood lymphocytes and in tissues of COVID-19 patients

Charvet¹,

Brunel²,

Pierquin³

et al. 2022

Preprint

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Patients with COVID-19 may develop abnormal inflammatory response and lymphopenia, followed in some cases by delayed-onset syndromes, often long-lasting after the initial SARS-CoV-2 infection. As viral infections may activate human endogenous retroviral elements (HERV), we studied the effect of SARS-CoV-2 on HERV-W and HERV-K envelope (ENV) expression, known to be involved in immunological and neurological pathogenesis of human diseases. Our results have showed that the exposure to SARS-CoV-2 virus activates early HERV-W and K transcription but only HERV-W ENV protein expression, in an infection- and ACE2-independent way within peripheral blood mononuclear cell cultures from one-third of healthy donors. Moreover, HERV-W ENV protein was significantly increased in serum and plasma of COVID-19 patients, correlating with its expression in CD3+ lymphocytes and with disease severity. Finally, HERV-W ENV was found expressed in post-mortem tissues of lungs, heart, brain olfactory bulb and nasal mucosa from acute COVID-19 patients in cell-types relevant for COVID-19-associated pathogenesis within affected organs, but different from those expressing of SARS-CoV-2 antigens. Altogether, the present study revealed that SARS-CoV-2 can induce HERV-W ENV expression in cells from individuals with symptomatic and severe COVID-19. Our data suggest that HERV-W ENV is likely to be involved in pathogenic features underlying symptoms of acute and post-acute COVID. It highlights the importance to further understand patients genetic susceptibility to HERV-W activation and the relevance of this pathogenic element as a prognostic marker and a therapeutic target in COVID-19 associated syndromes.

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Meta-Analysis and Structural Dynamics of the Emergence of Genetic Variants of SARS-CoV-2

Cited by 19 publications

References 53 publications

Learning From Biological and Computational Machines: Importance of SARS-CoV-2 Genomic Surveillance, Mutations and Risk Stratification

Learning From Biological and Computational Machines: Importance of SARS-CoV-2 Genomic Surveillance, Mutations and Risk Stratification

Reopening California: Seeking robust, non-dominated COVID-19 exit strategies

SARS-CoV-2 induces human endogenous retrovirus type W envelope protein expression in blood lymphocytes and in tissues of COVID-19 patients

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