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MeSH Disease

HGNC Genes

SARS-CoV-2 proteins

ProteinS (9)

NSP5 (4)

ProteinN (4)

NSP3 (1)

ProteinE (1)


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SARS-CoV-2 Proteins
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    TCA-soluble blood serum proteins of COVID-19 MESHD patients as possible predictive markers for the disease severity

    Authors: Andrii Orfin; Tamila Alexanyan; Svitlana Tkachuk Svitlana Tkachuk; Anatoliy Starodub; Taras Luchyshyn; Andriy Sibirny; Serhiy Souchelnytskyi; Yuriy Kit

    doi:10.1101/2021.04.07.21255063 Date: 2021-04-09 Source: medRxiv

    Coronavirus disease MESHD 19 ( COVID-19 MESHD) is a global health crisis on a planetary scale. COVID-19 MESHD in many people has mild or moderate manifestation, although significant number of people, especially the elderly, suffer heavy from this illness, which often resulting in death MESHD. There are reports of similarities in immune response between COVID-19 MESHD and some autoimmune diseases MESHD. Earlier, we have demonstrated that fraction of TCA-soluble blood serum proteins containing a 48 kDA fragment of unconvential Myosin C1 have linked with development of multiple sclerosis MESHD and rheumatoid arthritis MESHD. Here we analyze use of these proteins in determining the severity of disease in COVID-19 MESHD patients. We found that blood serum of COVID-19 MESHD patients in acute disease MESHD manifestation contains, in contrast to healthy individuals, the TCA-soluble proteins with molecular masses 48 kDa and 76 kDA which were identified as a short form of unconventional myosin 1c and a modified form of human serum albumin HGNC.

    Sudden rise in COVID-19 MESHD case fatality among young and middle-aged adults in the south of Brazil after identification of the novel B.1.1.28.1 ( P.1 HGNC) SARS-CoV-2 strain: analysis of data from the state of Parana

    Authors: Maria Helena Santos de Oliveira; Giuseppe Lippi; Brandon Michael Henry

    doi:10.1101/2021.03.24.21254046 Date: 2021-03-26 Source: medRxiv

    Brazil is currently suffering a deadly surge of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections MESHD, which has been attributed to the spread of a new strain known as P.1 HGNC (B.1.1.28.1). In this investigation, we analyzed coronavirus disease 2019 MESHD ( COVID-19 MESHD) public health data from Parana, the largest state in southern half of Brazil, between September 1, 2020 and March 17, 2021, to evaluate recent trends in case fatality rates in different age groups. A total of 553,518 cases of SARS-CoV-2, 8,853 currently registered as fatal, were finally included in our analysis. All age groups showed either decline or stabilization of the case fatality rates (CFRs) between September 2020 and January 2021. In February 2021, an increase in CFR for almost all age groups could be instead observed. All groups above 20 years of age showed statistically significant increases in CFR when diagnosed in February 2021 as opposed to January 2021. Patients aged 20-29 years experienced a tripling of their CFR, from 0.04% to 0.13%, while those aged 30-39, 40-49, 50-59 experienced approximate CFR doubling. Individuals between 20 and 29 years of age whose diagnosis was made in February 2021 had an over 3-fold higher risk of death MESHD compared to those diagnosed in January 2021 (Risk Ratio (RR): 3.15 [95%CI: 1.52-6.53], p<0.01), while those aged 30-39, 40-49, 50-59 years experienced 93% (1.93 [95%CI:1.31-2.85], p<0.01), 110% (RR: 2.10 [95%CI:1.62-2.72], p<0.01), and 80% (RR: 1.80 [95%CI:1.50-2.16], p<0.01) increases in risk of death MESHD, respectively. Notably, the observed CFR increase coincided with the second consecutive month of declining number of diagnosed SARS-CoV-2 cases. Taken together, these preliminary findings suggest significant increases in CFR in young and middle-aged adults after identification of a novel SARS-CoV-2 strain circulating in Brazil, and this should raise public health alarms, including the need for more aggressive local and regional public health interventions and faster vaccination.

    Estimating the impact of interventions against COVID-19 MESHD: from lockdown to vaccination

    Authors: James Thompson; Stephen Wattam

    doi:10.1101/2021.03.21.21254049 Date: 2021-03-26 Source: medRxiv

    Coronavirus disease 2019 MESHD ( COVID-19 MESHD) is an infectious disease of humans caused by severe acute respiratory syndrome coronavirus 2 MESHD (SARS-CoV-2). Since the first case was identified in China in December 2019 the disease has spread worldwide, leading to an ongoing pandemic. In this article, we present a detailed agent-based model of COVID-19 MESHD in Luxembourg, and use it to estimate the impact, on cases and deaths, of interventions including testing, contact tracing, lockdown, curfew and vaccination. Our model is based on collation, with agents performing activities and moving between locations accordingly. The model is highly heterogeneous, featuring spatial clustering, over 2000 behavioural types and a 10 minute time resolution. The model is validated against COVID-19 MESHD clinical monitoring data collected in Luxembourg in 2020. Our model predicts far fewer cases and deaths MESHD than the equivalent equation-based SEIR model. In particular, with $R_0 = 2.45$, the SEIR model infects 87% of the resident population while our agent-based model results, on average, in only around 23% of the resident population infected. Our simulations suggest that testing and contract tracing reduce cases substantially, but are much less effective at reducing deaths. Lockdowns appear very effective although costly, while the impact of an 11pm-6am curfew is relatively small. When vaccinating against a future outbreak, our results suggest that herd immunity can be achieved at relatively low levels, with substantial levels of protection achieved with only 30% of the population immune. When vaccinating in midst of an outbreak, the challenge is more difficult. In this context, we investigate the impact of vaccine efficacy, capacity, hesitancy and strategy. We conclude that, short of a permanent lockdown, vaccination is by far the most effective way to suppress and ultimately control the spread of COVID-19 MESHD.

    Forecasting the Epidemiological Impact of Coronavirus Disease MESHD ( COVID-19 MESHD): Pre-vaccination Era

    Authors: Saheed Oladele Amusat

    doi:10.1101/2021.03.17.21253791 Date: 2021-03-24 Source: medRxiv

    Background: During this pandemic, many studies have been published on the virology, diagnosis, prevention, and control of the novel coronavirus. However, fewer studies are currently available on the quantitative future epidemiological impacts. Therefore, the purpose of this study is to forecast the COVID-19 MESHD morbidities and associated-mortalities among the top 20 countries with the highest number of confirmed COVID-19 MESHD cases globally prior to vaccination intervention. Method: We conducted a secondary data analysis of the prospective geographic distribution of COVID-19 MESHD cases data worldwide as of 10 April 2020. The historical data was forecasted using Exponential-Smoothing to detect seasonality patterns and confidence intervals surrounding each predicted value in which 95 percent of the future points are expected to fall based on the forecast. Results: The total mean forecasted cases and deaths MESHD were 99,823 and 8,801. Interestingly, the US has the highest forecasted cases, deaths, and percentage cases-deaths ratio of 45,338, 2 358, and 5.20% respectively. China has the lowest cases, deaths, and percentage cases-deaths ratio -267, -2, and 0.75% respectively. In addition, France has the highest forecasted percentage cases-deaths ratio of 26.40% with forecasted cases, and deaths of 6,246, and 1,649 respectively. Conclusion Our study revealed the possibility of higher COVID-19 MESHD morbidities and associated-mortalities worldwide.

    Mortality in individuals treated with COVID-19 MESHD convalescent plasma varies with the geographic provenance of donors

    Authors: Katie L Kunze; Patrick W Johnson; Noud van Helmond; Jonathon W Senefeld; Molly M Petersen; Stephen A Klassen; Chad C Wiggins; Allan M Klompas; Katelyn A Bruno; John R Mills; Elitza S Theel; Matthew R Buras; Michael A Golafshar; Matthew A Sexton; Juan C Diaz Soto; Sarah E Baker; John R.A. Shepherd; Nicole C Verdun; Peter Marks; Nigel S Paneth; DeLisa Fairweather; R. Scott Wright; Camille M van Buskirk; Jeffrey L Winters; James R Stubbs; Robert F Rea; Vitaly Herasevich; Emily R Whelan; Andrew J Clayburn; Kathryn F Larson; Juan G Ripoll; Kylie J Andersen; Elizabeth R Lesser; Matthew N.P. Vogt; Joshua J Dennis; Riley J Regimbal; Philippe R Bauer; Janis E Blair; Arturo Casadevall; Rickey E Carter; Michael J Joyner

    doi:10.1101/2021.03.19.21253975 Date: 2021-03-22 Source: medRxiv

    Treatment and prevention of coronavirus disease 2019 MESHD ( COVID-19 MESHD) have attempted to harness the immune response to severe acute respiratory syndrome coronavirus 2 MESHD (SARS-CoV-2) including the development of successful COVID-19 MESHD vaccines and therapeutics (e.g., Remdesivir, convalescent plasma [CP]). Evidence that SARS-CoV-2 exists as quasispecies evolving locally suggests that immunological differences may exist that could impact the effectiveness of antibody-based treatments and vaccines. Regional variants of SARS-CoV-2 were reported in the USA beginning in November 2020 but were likely present earlier. There is available evidence that the effectiveness of CP obtained from donors infected with earlier strains in the pandemic may be reduced when tested for neutralization against newer SARS-Cov-2 variants. Using data from the Expanded Access Program to convalescent plasma, we used a gradient-boosting machine to identify predictors of 30-day morality and a series of regression models to estimate the relative risk of death MESHD at 30 days post-transfusion for those receiving near sourced plasma (defined as plasma transported [≤] 150 miles) vs. distantly sourced plasma (> 150 miles). Our results show a lower risk of death MESHD at 30 days post-transfusion for near sourced plasma. Additional analyses stratified by disease severity, time to treatment, and donor region further supported these findings. The results of this study suggest that near sourced plasma is superior to distantly sourced plasma, which has implications for interpreting the results of clinical studies and designing effective treatment of COVID-19 MESHD patients as additional local variant are likely to emerge.

    Sarcopenic obesity MESHD and the risk of hospitalisation or death from COVID-19 MESHD: findings from UK Biobank

    Authors: Thomas Wilkinson; Thomas Yates; Luke A Baker; Francesco Zaccardi; Alice C Smith

    doi:10.1101/2021.03.19.21253945 Date: 2021-03-20 Source: medRxiv

    Background Coronavirus disease-2019 ( COVID-19 MESHD) is an infectious disease MESHD caused by severe acute respiratory syndrome coronavirus 2 MESHD (SARS;CoV-2 virus). The role of skeletal muscle mass in modulating immune response is well documented. Whilst obesity MESHD is well-established as a key factor in COVID-19 MESHD infection and outcome, no study has examined the influence of both sarcopenia MESHD (low muscle mass) and obesity MESHD, termed sarcopenic obesity MESHD on COVID-19 MESHD risk. Methods This study uses data from UK Biobank. Probable sarcopenia MESHD was defined as low handgrip strength. Sarcopenic obesity MESHD was mutually exclusively defined as the presence of obesity MESHD and low muscle mass (based on two established criteria: appendicular lean mass (ALM) adjusted for either: 1) height and 2) body mass index (BMI)). Severe COVID-19 MESHD was defined by a positive test result in a hospital setting or death MESHD with a primary cause reported as COVID-19 MESHD. Fully adjusted logistic regression models were used to analyse the associations between sarcopenic status MESHD and severe COVID-19 MESHD. This work was conducted under UK Biobank application number 52553. Results We analysed data from 490,301 UK Biobank participants. 2203 (0.4%) had severe COVID-19 infection MESHD. Individuals with probable sarcopenia were 64% more likely to have had severe COVID-19 MESHD infection (odds ratio (OR) 1.638; P

    Identification of guanylyltransferase activity in the SARS-CoV-2 RNA polymerase

    Authors: Alexander P Walker; Haitian Fan; Jeremy R Keown; Jonathan Grimes; Ervin Fodor

    doi:10.1101/2021.03.17.435913 Date: 2021-03-18 Source: bioRxiv

    SARS-CoV-2 is a positive-sense RNA virus that is responsible for the ongoing Coronavirus Disease MESHD Coronavirus Disease 2019 MESHD ( COVID-19 MESHD) pandemic, which continues to cause significant morbidity, mortality and economic strain. SARS-CoV-2 can cause severe respiratory disease MESHD and death MESHD in humans, highlighting the need for effective antiviral therapies. The RNA synthesis machinery of SARS-CoV-2 is an ideal drug target and consists of non-structural protein 12 PROTEIN (nsp12), which is directly responsible for RNA synthesis, and numerous co-factors that are involved in RNA proofreading and 5' capping of viral mRNAs. The formation of the 5' cap-1 HGNC structure is known to require a guanylyltransferase (GTase) as well as 5' triphosphatase and methyltransferase activities. However, the mechanism of SARS-CoV-2 mRNA capping remains poorly understood. Here we show that the SARS-CoV-2 RNA polymerase nsp12 functions as a GTase. We characterise this GTase activity and find that the nsp12 NiRAN (nidovirus RdRP PROTEIN-associated nucleotidyltransferase) domain is responsible for carrying out the addition of a GTP nucleotide to the 5' end of viral RNA via a 5' to 5' triphosphate linkage. We also show that remdesivir triphosphate, the active form of the antiviral drug remdesivir, inhibits the SARS-CoV-2 GTase reaction as efficiently as RNA polymerase activity. These data improve understanding of coronavirus mRNA cap synthesis and highlight a new target for novel or repurposed antiviral drugs against SARS-CoV-2.

    Forecasting the Spread of COVID-19 MESHD and ICU Requirements

    Authors: Prajoy Podder; Aditya Khamparia; M. Rubaiyat Hossain Mondal; Mohammad Atikur Rahman; Subrato Bharati

    id:10.20944/preprints202103.0447.v1 Date: 2021-03-17 Source: Preprints.org

    Since December 2019, the world is fighting against coronavirus disease MESHD ( COVID-19 MESHD). This disease is caused by a novel coronavirus termed as severe acute respiratory syndrome coronavirus 2 MESHD (SARS-CoV-2). This work focuses on the applications of machine learning algorithms in the context of COVID-19 MESHD. Firstly, regression analysis is performed to model the number of confirmed cases and death MESHD cases. Our experiments show that autoregressive integrated moving average (ARIMA) can reliably model the increase in the number of confirmed cases and can predict future cases. Secondly, a number of classifiers are used to predict whether a COVID-19 MESHD patient needs to be admitted to an intensive care unit (ICU) or semi-ICU. For this, classification algorithms are applied to a dataset having 5644 samples. Using this dataset, the most significant attributes are selected using features selection by ExtraTrees classifier, and Proteina C reativa (mg/dL) is found to be the highest-ranked feature. In our experiments, random forest, logistic regression, support vector machine, XGBoost, stacking and voting classifiers are applied to the top 10 selected attributes of the dataset. Results show that random forest and hard voting classifiers achieve the highest classification accuracy values near 98%, and the highest recall value of 98% in predicting the need for admission into ICU/semi ICU units.

    3D genomic capture of regulatory immuno-genetic profiles in COVID-19 MESHD patients for prognosis of severe COVID disease outcome MESHD

    Authors: Ewan Hunter; Christina Koutsothanasi; Adam Wilson; Francisco Coroado Santos; Matthew Salter; Ryan Powell; Ann Dring; Paulina Brajer; Benedict Egan; Jurjen Westra; Aroul Ramadass; William Messner; Amanda Brunton; Zoe Lyski; Rama Vancheeswaran; Andrew Barlow; Dmitri Pchejetski; Alexandre Akoulitchev

    doi:10.1101/2021.03.14.435295 Date: 2021-03-16 Source: bioRxiv

    Human infection with the SARS-CoV-2 virus leads to coronavirus disease MESHD ( COVID-19 MESHD). A striking characteristic of COVID-19 MESHD infection in humans is the highly variable host response and the diverse clinical outcomes, ranging from clinically asymptomatic to severe immune reactions leading to hospitalization and death MESHD. Here we used a 3D genomic approach to analyse blood samples at the time of COVID diagnosis, from a global cohort of 80 COVID-19 MESHD patients, with different degrees of clinical disease outcomes. Using 3D whole genome EpiSwitch(R) arrays to generate over 1 million data points per patient, we identified a distinct and measurable set of differences in genomic organization at immune-related loci that demonstrated prognostic power at baseline to stratify patients with mild forms of illness and those with severe forms that required hospitalization and intensive care unit (ICU) support. Further analysis revealed both well established and new COVID-related dysregulated pathways and loci, including innate and adaptive immunity; ACE2 HGNC; olfactory, G{beta}{psi}, Ca2+ and nitric oxide (NO) signalling; prostaglandin E2 (PGE2), the acute inflammatory cytokine CCL3 HGNC, and the T-cell derived chemotactic cytokine CCL5 HGNC. We identified potential therapeutic agents for mitigation of severe disease outcome, with several already being tested independently, including mTOR HGNC inhibitors (rapamycin and tacrolimus) and general immunosuppressants (dexamethasone and hydrocortisone). Machine learning algorithms based on established EpiSwitch(R) methodology further identified a subset of 3D genomic changes that could be used as prognostic molecular biomarker leads for the development of a COVID-19 MESHD disease severity test.

    An Extended COVID-19 MESHD Epidemiological Model with Vaccination and Multiple Interventions for Controlling COVID-19 MESHD Outbreaks in the UK

    Authors: Shuhao Zhang; Gaoshan Bi; Yun Yang; Jun Qi; Shujun Li; Xuxin Mao; Ruoling Peng; Po Yang

    doi:10.1101/2021.03.10.21252748 Date: 2021-03-12 Source: medRxiv

    There has been a second outbreak of the Coronavirus disease MESHD ( COVID-19 MESHD) in the UK in 2020. In this situation, the UK re-implemented the lockdown intervention strategy. Different from the first COVID outbreak, the second outbreak is accompanied by two new situations: 1) There are at least three new variant strains in the UK and they are more infectious than the original strain. The mutant strain considered in the experimental simulation accounts for the majority of all strains of the mutant infection in the UK. 2) The official start of a vaccination programme in the UK started in mid-December 2020. As the date for lifting the third lockdown approaches, what kind of intervention measures will the UK continue to take: curb the spread of the COVID epidemic, reduce medical needs and allow people to return to normal life and revitalize the national economy as quickly as possible. Targeting at this problem, this article conduct a feasibility study by defining the mathematical model SEMCVRD (Susceptible [S], Exposed [E] (infected but asymptomatic), Mild [M] and Critical [C] (mild cases, severe and critical cases), [V] (vaccinated), Recovered [R] and Deceased [D]), which is expanded the traditional SEIR (Susceptible [S], Exposed [E], Infectious [I], Recovered [R]) model by adding two key features: the mixed infection of the mutant strain and the original strain and the addition of a new group who have been vaccinated. The model uses a public data set for fitting and evaluation. The dataset contains daily new infections, new deaths and daily vaccination in the UK from February 2020 to February 2021. Based on the simulation results, the following content was found : 1) There are simulated the mixed infection of the new mutant virus and the original virus in the UK. Under the assumption that the vaccine is effective against the new virus, continuing to promote the injection of the vaccine in society can effectively inhibit the spread and infection of the new mutant virus. Predicting that if UK could continuously implement insensitive suppression, COVID-19 MESHD epidemic would be able to control by 9th April 2021 and would be nearly ended by 1st May 2020. 2) With the increasing number of people vaccinated and immunized against the virus, the lifting of the third lockdown in the UK is coming. Using a phased and progressive lifting intervention strategy with an intensity of 3 is our best choice at present. Under this strategy, on 30th June 2021, the total number of infections in the UK will be limited to 4.2 million and the total number of deaths in the UK is 135 thousand. If the lockdown is lifted directly, the total number of infections in the UK will increase to 8 million and the total number of deaths in the UK will be 279 thousand on 30th June 2021. It can be seen from the above that our strategy compared to directly lifting the lockdown can greatly reduce the total number of infections and deaths MESHD. People can return to normal life and social distancing after four months. The epidemic will nearly end in 6th June 2021 (The sign of the end: the number of new infections per day is less than 1,000 and the number of new deaths per day is less than 35). In addition, according to our prediction, under this kind of intervention, the UK will not experience a shortage of medical resources as it did in the first half of 2020. 3) In the case that it is possible to provide people with 600 thousand vaccinations(double the quantity now provided) every day, a higher intensity (intensity 5) Phase intervention strategy can be trying to nearly end the epidemic earlier (25th May 2021) and restore peoples normal life and social distance.

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MeSH Disease
HGNC Genes
SARS-CoV-2 Proteins


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