scholarly journals Three SARS-CoV-2 reinfection cases by the new Variant of Concern (VOC) P.1/501Y.V3

2021 ◽  
Author(s):  
Felipe Naveca ◽  
Cristiano da Costa ◽  
Valdinete Nascimento ◽  
Victor Souza ◽  
André Corado ◽  
...  
Keyword(s):  
Immune Escape ◽  
Severe Disease ◽  
Genomic Analysis ◽  
Severe Illness ◽  
Infection Event ◽  
New Variant ◽  
Recent Emergence ◽  
Potential Impact ◽  
Amazonas State ◽  
Generation Sequencing

Abstract The SARS-CoV-2 lineage B.1.1.28 has been evolving in Brazil since February 2020 giving origin to multiple local clades including the new Variant of Concern (VOC) designated P.1 or 501Y.V3. The recent emergence of sub-lineages with convergent mutations in the spike (S) protein raises concern about the potential impact on viral infectivity and immune escape. We describe here the first three confirmed SARS-CoV-2 reinfections cases with the new VOC P.1 in residents of the Amazonas state, Brazil. Three female patients, 29, 40, and 50-year-old, were RT-PCR confirmed for SARS-CoV-2 on two occasions, with at least 92 days apart. Next-generation sequencing and phylogenetic analysis were conducted to precisely access the SARS-CoV-2 lineages of each infection event. SARS-CoV-2 genomic analysis confirmed three cases of reinfections caused by the VOC P.1 in patients that were primo-infected by distinct viral lineages 3–9 months earlier. Case 1 (29-year-old) was positive on March 24, 2020 (lineage B.1.195) and then on December 30, 2020 (lineage P.1); case 2 (50-year-old) was positive on October 19, 2020 (lineage B.1.1.33) and on January 19, 2021 (lineage P.1); case 3 (40-year-old) was positive on April 22, 2020 (lineage B.1.195) and on January 29, 2021 (lineage P.1). The three patients displayed low mean Ct values (< 22) at nasopharyngeal samples and reported less severe illness during reinfection. The present study provides the first evidence of the new VOC P.1 causing multiple reinfections during the second epidemic peak in the Amazonas state. Our findings suggest that reinfected individuals may have been infectious. Although immune responses induced by natural infections do not necessarily prevent subsequent infections by the VOC P.1, they may still protect from severe disease.

scholarly journals COVID-19 immunologic and toxicological implication: Innate immune sensor and immune escape

2021 ◽  
Vol 5 (1) ◽  
pp. 001-017
Author(s):  
M Luisetto ◽  
Ilman Ahnaf ◽  
Khan Farhan Ahmad ◽  
Edbey Khaled ◽  
Hamid Gamal Abdul ◽  
...  
Keyword(s):  
Immune System ◽  
Immune Escape ◽  
Severe Disease ◽  
Point Of View ◽  
Innate Immune ◽  
Severe Condition ◽  
New Variant ◽  
Rapid Emergence ◽  
New Strategies ◽  
Viral Respiratory

Related COVID-19 and new Variant and treatment like vaccine it is relevant to deeply verify the immunologic implication and in a special way regarding the innate immune sensor system and the evasion of the immune system. This can be crucial to search for new strategies to fight this severe disease under a Toxicology-antidotes point of view. The rapid emergence of a new variant is under study by researchers because some of these show different responses to antibodies as reported in literature (vaccine efficacy?). In this article after a review part it is submitted a collection of hypothesis of solution to contrast COVID-19. Spread and mortality and project hypothesis. A new toxicological approach also in a viral respiratory disease can be a novelty to adequately fight this severe condition and this focusing not only towards specific immunity but also a specific measures. A toxicological approach in drug- vaccine like products designing makes it possible to get the clinical outcomes needed.

Personalized stratification of back to work risk amidst COVID-19: A machine learning approach (Preprint)

2020 ◽  
Author(s):  
Carson Lam ◽  
Jacob Calvert ◽  
Gina Barnes ◽  
Emily Pellegrini ◽  
Anna Lynn-Palevsky ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Risk ◽  
Learning Algorithm ◽  
Severe Disease ◽  
High Specificity ◽  
Population Level ◽  
The United States ◽  
Health Condition ◽  
Available P ◽  
Severe Illness

BACKGROUND In the wake of COVID-19, the United States has developed a three stage plan to outline the parameters to determine when states may reopen businesses and ease travel restrictions. The guidelines also identify subpopulations of Americans that should continue to stay at home due to being at high risk for severe disease should they contract COVID-19. These guidelines were based on population level demographics, rather than individual-level risk factors. As such, they may misidentify individuals at high risk for severe illness and who should therefore not return to work until vaccination or widespread serological testing is available. OBJECTIVE This study evaluated a machine learning algorithm for the prediction of serious illness due to COVID-19 using inpatient data collected from electronic health records. METHODS The algorithm was trained to identify patients for whom a diagnosis of COVID-19 was likely to result in hospitalization, and compared against four U.S policy-based criteria: age over 65, having a serious underlying health condition, age over 65 or having a serious underlying health condition, and age over 65 and having a serious underlying health condition. RESULTS This algorithm identified 80% of patients at risk for hospitalization due to COVID-19, versus at most 62% that are identified by government guidelines. The algorithm also achieved a high specificity of 95%, outperforming government guidelines. CONCLUSIONS This algorithm may help to enable a broad reopening of the American economy while ensuring that patients at high risk for serious disease remain home until vaccination and testing become available.

scholarly journals Hematologic, biochemical and immune biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis

2020 ◽  
Vol 58 (7) ◽  
pp. 1021-1028 ◽  
Author(s):  
Brandon Michael Henry ◽  
Maria Helena Santos de Oliveira ◽  
Stefanie Benoit ◽  
Mario Plebani ◽  
Giuseppe Lippi
Keyword(s):  
Serum Ferritin ◽  
Weighted Mean Difference ◽  
Meta Analysis ◽  
Severe Disease ◽  
Severe Illness ◽  
China National Knowledge Infrastructure ◽  
Discriminative Ability ◽  
Laboratory Findings ◽  
Liver And Kidney ◽  
Wbc Count

AbstractBackgroundAs coronavirus disease 2019 (COVID-19) pandemic rages on, there is urgent need for identification of clinical and laboratory predictors for progression towards severe and fatal forms of this illness. In this study we aimed to evaluate the discriminative ability of hematologic, biochemical and immunologic biomarkers in patients with and without the severe or fatal forms of COVID-19.MethodsAn electronic search in Medline (PubMed interface), Scopus, Web of Science and China National Knowledge Infrastructure (CNKI) was performed, to identify studies reporting on laboratory abnormalities in patients with COVID-19. Studies were divided into two separate cohorts for analysis: severity (severe vs. non-severe and mortality, i.e. non-survivors vs. survivors). Data was pooled into a meta-analysis to estimate weighted mean difference (WMD) with 95% confidence interval (95% CI) for each laboratory parameter.ResultsA total number of 21 studies was included, totaling 3377 patients and 33 laboratory parameters. While 18 studies (n = 2984) compared laboratory findings between patients with severe and non-severe COVID-19, the other three (n = 393) compared survivors and non-survivors of the disease and were thus analyzed separately. Patients with severe and fatal disease had significantly increased white blood cell (WBC) count, and decreased lymphocyte and platelet counts compared to non-severe disease and survivors. Biomarkers of inflammation, cardiac and muscle injury, liver and kidney function and coagulation measures were also significantly elevated in patients with both severe and fatal COVID-19. Interleukins 6 (IL-6) and 10 (IL-10) and serum ferritin were strong discriminators for severe disease.ConclusionsSeveral biomarkers which may potentially aid in risk stratification models for predicting severe and fatal COVID-19 were identified. In hospitalized patients with respiratory distress, we recommend clinicians closely monitor WBC count, lymphocyte count, platelet count, IL-6 and serum ferritin as markers for potential progression to critical illness.

scholarly journals Severely ill COVID-19 patients display impaired exhaustion features in SARS-CoV-2-reactive CD8+ T cells

2021 ◽  
Vol 6 (55) ◽  
pp. eabe4782 ◽  
Author(s):  
Anthony Kusnadi ◽  
Ciro Ramírez-Suástegui ◽  
Vicente Fajardo ◽  
Serena J Chee ◽  
Benjamin J Meckiff ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Single Cell ◽  
Healthy Subjects ◽  
Single Cell Analysis ◽  
Severe Disease ◽  
T Cell Response ◽  
Severe Illness ◽  
Syncytial Virus ◽  
Apoptotic Pathways

The molecular properties of CD8+ T cells that respond to SARS-CoV-2 infection are not fully known. Here, we report on the single-cell transcriptomes of >80,000 virus-reactive CD8+ T cells, obtained using a modified Antigen-Reactive T cell Enrichment (ARTE) assay, from 39 COVID-19 patients and 10 healthy subjects. COVID-19 patients segregated into two groups based on whether the dominant CD8+ T cell response to SARS-CoV-2 was ‘exhausted’ or not. SARS-CoV-2-reactive cells in the exhausted subset were increased in frequency and displayed lesser cytotoxicity and inflammatory features in COVID-19 patients with mild compared to severe illness. In contrast, SARS-CoV-2-reactive cells in the dominant non-exhausted subset from patients with severe disease showed enrichment of transcripts linked to co-stimulation, pro-survival NF-κB signaling, and anti-apoptotic pathways, suggesting the generation of robust CD8+ T cell memory responses in patients with severe COVID-19 illness. CD8+ T cells reactive to influenza and respiratory syncytial virus from healthy subjects displayed polyfunctional features and enhanced glycolysis. Cells with such features were largely absent in SARS-CoV-2-reactive cells from both COVID-19 patients and healthy controls non-exposed to SARS-CoV-2. Overall, our single-cell analysis revealed substantial diversity in the nature of CD8+ T cells responding to SARS-CoV-2.

scholarly journals Ensemble forecast of COVID-19 in Karnataka for vulnerability assessment and policy interventions

2021 ◽  
Author(s):  
Sashikumaar Ganesan ◽  
Deepak Subramani ◽  
Thivin Anandh ◽  
Divij Ghose ◽  
Giridhara R Babu
Keyword(s):  
Immune Escape ◽  
Ensemble Forecast ◽  
Disease Spread ◽  
Critical Parameters ◽  
New Wave ◽  
Public Health Response ◽  
Causal Factors ◽  
Appropriate Behavior ◽  
Policy Interventions ◽  
New Variant

We present an ensemble forecast for Wave-3 of COVID-19 in the state of Karnataka, India, using the IISc Population Balance Model for infectious disease spread. The reported data of confirmed, recovered, and deceased cases in Karnataka from 1 July 2020 to 4 July 2021 is utilized to tune the model's parameters, and an ensemble forecast is done from 5 July 2021 to 30 June 2022. The ensemble is built with 972 members by varying seven critical parameters that quantify the uncertainty in the spread dynamics (antibody waning, viral mutation) and interventions (pharmaceutical, non-pharmaceutical). The probability of Wave-3, the peak date distribution, and the peak caseload distribution are estimated from the ensemble forecast. Our analysis shows that the most significant causal factors are compliance to Covid-appropriate behavior, daily vaccination rate, and the immune escape new variant emergence-time. These causal factors determine when and how severe the Wave-3 of COVID-19 would be in Karnataka. We observe that when compliance to Covid-Appropriate Behavior is good (i.e., lockdown-like compliance), the emergence of new immune-escape variants beyond Sep '21 is unlikely to induce a new wave. A new wave is inevitable when compliance to Covid-Appropriate Behavior is only partial. Increasing the daily vaccination rates reduces the peak active caseload at Wave-3. Consequently, the hospitalization, ICU, and Oxygen requirements also decrease. Compared to Wave-2, the ensemble forecast indicates that the number of daily confirmed cases of children (0-17 years) at Wave-3's peak could be seven times more on average. Our results provide insights to plan science-informed policy interventions and public health response.

scholarly journals The Predictive Value of Myoglobin for COVID-19-Related Adverse Outcomes: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 8 ◽  
Author(s):  
Chaoqun Ma ◽  
Dingyuan Tu ◽  
Jiawei Gu ◽  
Qiang Xu ◽  
Pan Hou ◽  
...  
Keyword(s):  
Troponin I ◽  
Meta Analysis ◽  
Severe Disease ◽  
Cardiac Injury ◽  
Case Fatality ◽  
Adverse Outcomes ◽  
Cardiac Biomarkers ◽  
Severe Illness ◽  
Poor Outcomes ◽  
Meta Analyses

Objective: Cardiac injury is detected in numerous patients with coronavirus disease 2019 (COVID-19) and has been demonstrated to be closely related to poor outcomes. However, an optimal cardiac biomarker for predicting COVID-19 prognosis has not been identified.Methods: The PubMed, Web of Science, and Embase databases were searched for published articles between December 1, 2019 and September 8, 2021. Eligible studies that examined the anomalies of different cardiac biomarkers in patients with COVID-19 were included. The prevalence and odds ratios (ORs) were extracted. Summary estimates and the corresponding 95% confidence intervals (95% CIs) were obtained through meta-analyses.Results: A total of 63 studies, with 64,319 patients with COVID-19, were enrolled in this meta-analysis. The prevalence of elevated cardiac troponin I (cTnI) and myoglobin (Mb) in the general population with COVID-19 was 22.9 (19–27%) and 13.5% (10.6–16.4%), respectively. However, the presence of elevated Mb was more common than elevated cTnI in patients with severe COVID-19 [37.7 (23.3–52.1%) vs.30.7% (24.7–37.1%)]. Moreover, compared with cTnI, the elevation of Mb also demonstrated tendency of higher correlation with case-severity rate (Mb, r = 13.9 vs. cTnI, r = 3.93) and case-fatality rate (Mb, r = 15.42 vs. cTnI, r = 3.04). Notably, elevated Mb level was also associated with higher odds of severe illness [Mb, OR = 13.75 (10.2–18.54) vs. cTnI, OR = 7.06 (3.94–12.65)] and mortality [Mb, OR = 13.49 (9.3–19.58) vs. cTnI, OR = 7.75 (4.4–13.66)] than cTnI.Conclusions: Patients with COVID-19 and elevated Mb levels are at significantly higher risk of severe disease and mortality. Elevation of Mb may serve as a marker for predicting COVID-19-related adverse outcomes.Prospero Registration Number:https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020175133, CRD42020175133.

scholarly journals Could docosahexaenoic acid (DHA), found in breast milk and artificial baby milks, protect infants and children from COVID-19 and make them less susceptible to COVID-19-related severe illness, as well as treat adult COVID-19 patients in combination with retinoic acid? A plan for observation and intervention

2021 ◽  
Author(s):  
Mahmoud Ramadan Elkazzaz ◽  
Amr kamel khalil Ahmed
Keyword(s):  
Retinoic Acid ◽  
Breast Milk ◽  
Docosahexaenoic Acid ◽  
Binding Affinity ◽  
Active Sites ◽  
Severe Disease ◽  
Gastrointestinal Symptoms ◽  
Influenza Viruses ◽  
Severe Illness ◽  
Cytokine Storm

Abstract SARS-CoV-2, which causes COVID-19, is a new virus that has spread fast over the world. The severity of COVID-19 at different ages has been a notable and constant observation: severity, the requirement for hospitalization, and mortality all grow sharply with age, although severe disease and death are uncommon in children and young adults.. The majority of children infected with SARS-CoV-2 are asymptomatic or have moderate symptoms, which include fever, cough, pharyngitis, gastrointestinal symptoms, and changes in taste and smell. The question of whether children are less likely to be infected with SARS-CoV-2 is still being debated. Children make up only 1 to 2% of all SARS-CoV-2 cases, according to large epidemiological research. these numbers are heavily, depend on testing criteria, and in many reports, testing was limited to those who were symptomatic or required hospitalization, which is less common in children.. According to certain research, children are just as likely as adults to contract SARS-CoV-2.9. Recent research suggests that children are less likely to become infected after coming into touch with a SARS-CoV-2-positive person.According to some reports, children and adolescents have similar virus loads and are hence just as likely to transmit SARS-CoV-2 as adults. Furthermore, the viral load in asymptomatic and symptomatic people may be identical. Reassuringly, transmission of the virus from children to other children or adults in schools has been infrequent.Children are less likely to be infected with SARS-CoV-2 and have less severe symptoms, which is similar to what has been observed with SARS-CoV-1 and Middle East respiratory disease (MERS)-CoV. Infection with most other respiratory viruses (e.g., respiratory syncytial virus (RSV), metapneumovirus, parainfluenza, or influenza viruses), on the other hand, has a far higher prevalence and severity in youngsters. Dr. Mahmoud Elkazzaz and Dr Amr kamel khalil Ahmed, the lead investigators of this observational study, recently published a preprint that demonstrated Docosahexaenoic acid (DHA) had a high binding affinity and greatest interactions with ACE2 active sites, as well as a moderate binding affinity and moderate interactions with the active sites of IL-6. The Docosahexaenoic acid (DHA) interacts with different active sites of IL6 and ACE2 which are involved in direct or indirect contacts with the ACE2 and IL-6 receptors which might act as potential blockers of functional ACE2 and IL-6 receptor complex.. A study proposed, a clinical benefit of targeting IL-17A signaling and the synergic inflammatory cytokine IL-6 to manage COVID-19 patients, particularly those presenting with cytokine storm syndrome.Hypercytokinemia, caused by notably high pro-inflammatory cytokines such as interleukin (IL)-1B, IL-6, IL-8, and IL-17, is mostly linked to the worsened clinical presentation of COVID-19 patients(14). In PBMCs from individuals with relapsing-remitting multiple sclerosis, a combination of docosahexaenoic acid (DHA) and all-trans-retinoic acid (ATRA) inhibits IL-17 gene expression.ConclusionsDocosahexaenoic acid (DHA) was detected in abundance in breast milk and other algal sources milk supplement used for newborns and children's feeding. As a result, we believe that docosahexaenoic acid (DHA) may protect children and newborns thorough competing with COVID-19 for ACE2 receptors and inhibiting IL-6 activity and may possibly help them avoid a cytokine storm and save their lives through inhibiting IL-6 and preventing SARS- CoV-2 RBD attachment to ACE2. In addition to IL-17 was fond to increase COVID-19 inflammatory complication in this case DHA combined with retinoic acid is expected to be effective in inhibiting IL-6 and IL-17.

scholarly journals Prognosis of COVID-19 Pneumonia Can Be Early Predicted Combining Age-Adjusted Charlson Comorbidity Index, CRB Score and Baseline Oxygen Saturation.

2021 ◽  
Author(s):  
Pilar Nuevo-Ortega ◽  
Carmen Reina-Artacho ◽  
Francisco Dominguez-Moreno ◽  
Victor Manuel Becerra-Muñoz ◽  
Luis Ruiz-Del-Fresno ◽  
...  
Keyword(s):  
Oxygen Saturation ◽  
Charlson Comorbidity Index ◽  
Severe Disease ◽  
Hospital Environment ◽  
Severe Illness ◽  
Comorbidity Index ◽  
Clinical Tools ◽  
Discharge From Hospital ◽  
Statistical Criteria

Abstract Background: In potentially severe diseases in general and COVID-19 in particular, it is vital to early identify those patients who are going to develop complications. The last update of a recent living systematic review dedicated to predictive models in COVID-19,[1] critically appraises 145 models, 8 of them focused on prediction of severe disease and 23 on mortality. Unfortunately, in all 145 models, they found a risk of bias significant enough to finally "not recommend any for clinical use". Authors suggest concentrating on avoiding biases in sampling and prioritising the study of already identified predictive factors, rather than the identification of new ones that are often dependent on the database. Our objective is to develop a model to predict which patients with COVID-19 pneumonia are at high risk of developing severe illness or dying, using basic and validated clinical tools.Methods: prospective cohort of consecutive patients admitted in a teaching hospital during the “first wave” of the COVID-19 pandemic. Follow-up to discharge from hospital. Multiple logistic regression selecting variables according to clinical and statistical criteria. Results: 404 consecutive patients were evaluated, 392 (97%) completed follow-up. Mean age was 61 years; 59% were men. The median burden of comorbidity was 2 points in the Age-adjusted Charlson Comorbidity Index, CRB was abnormal in 18% of patients and basal oxygen saturation on admission lower than 90% in 18%. A model composed of Age-adjusted Charlson Comorbidity Index, CRB score and basal oxygen saturation can predict unfavorable evolution or death with an area under the ROC curve of 0.85 (95% CI: 0.80-0.89), and 0.90 (95% CI: 0.86 to 0.94), respectively.Conclusion: prognosis of COVID-19 pneumonia can be predicted in the out-of-hospital environment using two classic prognostic scales and a pocket pulse oximeter.

scholarly journals Limited within-host diversity and tight transmission bottlenecks limit SARS-CoV-2 evolution in acutely infected individuals

2021 ◽  
Author(s):  
Katarina Braun ◽  
Gage Kahl Moreno ◽  
Cassia Wagner ◽  
Molly A. Accola ◽  
William M Rehrauer ◽  
...  
Keyword(s):  
Immune Escape ◽  
Acute Infection ◽  
Host Diversity ◽  
Recent Emergence ◽  
Novel Variants ◽  
Efficient Selection

The recent emergence of divergent SARS-CoV-2 lineages has raised concerns about the role of selection within individual hosts in propagating novel variants. Of particular concern are variants associated with immune escape and/or enhanced transmissibility. Though growing evidence suggests that novel variants can arise during prolonged infections, most infections are acute. Understanding the extent to which variants emerge and transmit among acutely infected hosts is therefore critical for predicting the pace at which variants resistant to vaccines or conferring increased transmissibility might emerge in the majority of SARS-CoV-2 infections. To characterize how within-host diversity is generated and propagated, we combine extensive laboratory and bioinformatic controls with metrics of within- and between-host diversity to 133 SARS-CoV-2 genomes from acutely infected individuals. We find that within-host diversity during acute infection is low and transmission bottlenecks are narrow, with very few viruses founding most infections. Within-host variants are rarely transmitted, even among individuals within the same household. Accordingly, we also find that within-host variants are rarely detected along phylogenetically linked infections in the broader community. Together, these findings suggest that efficient selection and transmission of novel SARS-CoV-2 variants is unlikely during typical, acute infection.

scholarly journals Integrative genomic analysis reveals cancer-associated mutations at diagnosis of CML in patients with high-risk disease

Blood ◽  
2018 ◽  
Vol 132 (9) ◽  
pp. 948-961 ◽  
Author(s):  
Susan Branford ◽  
Paul Wang ◽  
David T. Yeung ◽  
Daniel Thomson ◽  
Adrian Purins ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
High Risk ◽  
Genomic Analysis ◽  
Kinase Domain ◽  
Cancer Genes ◽  
High Risk Disease ◽  
Key Points ◽  
Kinase Domain Mutations ◽  
Poor Outcomes ◽  
Generation Sequencing

Key Points Next-generation sequencing revealed variants in cancer-associated genes at diagnosis of CML more frequently in patients with poor outcomes. All patients at BC had mutated cancer genes, including fusions, that predated BCR-ABL1 kinase domain mutations in a majority.

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