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1.
Front Med (Lausanne) ; 9: 802312, 2022.
Article in English | MEDLINE | ID: covidwho-1775693

ABSTRACT

Recent progress in genomics and bioinformatics technologies have allowed for the emergence of immunogenomics field. This intersection of immunology and genetics has broadened our understanding of how the immune system responds to infection and vaccination. While the immunogenetic basis of the huge clinical variability in response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is currently being extensively studied, the host genetic determinants of SARS-CoV-2 vaccines remain largely unknown. Previous reports evidenced that vaccines may not protect all populations or individuals equally, due to multiple host- and vaccine-specific factors. Several studies on vaccine response to measles, rubella, hepatitis B, smallpox, and influenza highlighted the contribution of genetic mutations or polymorphisms in modulating the innate and adaptive immunity following vaccination. Specifically, genetic variants in genes encoding virus receptors, antigen presentation, cytokine production, or related to immune cells activation and differentiation could influence how an individual responds to vaccination. Although such knowledge could be utilized to generate personalized vaccine strategies to optimize the vaccine response, studies in this filed are still scarce. Here, we briefly summarize the scientific literature related to the immunogenetic determinants of vaccine-induced immunity, highlighting the possible role of host genetics in response to SARS-CoV-2 vaccines as well.

2.
Nat Commun ; 13(1): 946, 2022 02 17.
Article in English | MEDLINE | ID: covidwho-1709499

ABSTRACT

COVID-19 complications still present a huge burden on healthcare systems and warrant predictive risk models to triage patients and inform early intervention. Here, we profile 893 plasma proteins from 50 severe and 50 mild-moderate COVID-19 patients, and 50 healthy controls, and show that 375 proteins are differentially expressed in the plasma of severe COVID-19 patients. These differentially expressed plasma proteins are implicated in the pathogenesis of COVID-19 and present targets for candidate drugs to prevent or treat severe complications. Based on the plasma proteomics and clinical lab tests, we also report a 12-plasma protein signature and a model of seven routine clinical tests that validate in an independent cohort as early risk predictors of COVID-19 severity and patient survival. The risk predictors and candidate drugs described in our study can be used and developed for personalized management of SARS-CoV-2 infected patients.


Subject(s)
Blood Proteins/analysis , COVID-19/mortality , COVID-19/pathology , Severity of Illness Index , Adult , COVID-19/drug therapy , Cytokines/blood , Female , Humans , Male , Middle Aged , Prognosis , Proteomics/methods , SARS-CoV-2/drug effects , Young Adult
3.
Immunogenetics ; 74(2): 213-229, 2022 04.
Article in English | MEDLINE | ID: covidwho-1616116

ABSTRACT

Cross-reactivity between different human coronaviruses (HCoVs) might contribute to COVID-19 outcomes. Here, we aimed to predict conserved peptides among different HCoVs that could elicit cross-reacting B cell and T cell responses. Three hundred fifty-one full-genome sequences of HCoVs, including SARS-CoV-2 (51), SARS-CoV-1 (50), MERS-CoV (50), and common cold species OC43 (50), NL63 (50), 229E (50), and HKU1 (50) were downloaded aligned using Geneious Prime 20.20. Identification of epitopes in the conserved regions of HCoVs was carried out using the Immune Epitope Database (IEDB) to predict B- and T-cell epitopes. Further, we identified sequences that bind multiple common MHC and modeled the three-dimensional structures of the protein regions. The search yielded 73 linear and 35 discontinuous epitopes. A total of 16 B-cell and 19 T-cell epitopes were predicted through a comprehensive bioinformatic screening of conserved regions derived from HCoVs. The 16 potentially cross-reactive B-cell epitopes included 12 human proteins and four viral proteins among the linear epitopes. Likewise, we identified 19 potentially cross-reactive T-cell epitopes covering viral proteins. Interestingly, two conserved regions: LSFVSLAICFVIEQF (NSP2) and VVHSVNSLVSSMEVQSL (spike), contained several matches that were described epitopes for SARS-CoV. Most of the predicted B cells were buried within the SARS-CoV-2 protein regions' functional domains, whereas T-cell stretched close to the functional domains. Additionally, most SARS-CoV-2 predicted peptides (80%) bound to different HLA types associated with autoimmune diseases. We identified a set of potential B cell and T cell epitopes derived from the HCoVs that could contribute to different diseases manifestation, including autoimmune disorders.


Subject(s)
Autoimmune Diseases , COVID-19 , Autoimmunity , Epitopes, T-Lymphocyte , Humans , Immunodominant Epitopes , SARS-CoV-2
4.
Vaccines (Basel) ; 9(10)2021 Oct 12.
Article in English | MEDLINE | ID: covidwho-1463870

ABSTRACT

The COVID-19 pandemic is still posing a devastating threat to social life and economics. Despite the modest decrease in the number of cases during September-November 2020, the number of active cases is on the rise again. This increase was associated with the emergence and spread of the new SARS-CoV-2 variants of concern (VOCs), such as the U.K. (B1.1.7), South Africa (B1.351), Brazil (P1), and Indian (B1.617.2) strains. The rapid spread of these new variants has raised concerns about the multiple waves of infections and the effectiveness of available vaccines. In this review, we discuss SARS-CoV-2 reinfection rates in previously infected and vaccinated individuals in relation to humoral responses. Overall, a limited number of reinfection cases have been reported worldwide, suggesting long protective immunity. Most reinfected patients were asymptomatic during the second episode of infection. Reinfection was attributed to several viral and/or host factors, including (i) underlying immunological comorbidities; (ii) low antibody titers due to the primary infection or vaccination; (iii) rapid decline in antibody response after infection or vaccination; and (iv) reinfection with a different SARS-CoV-2 variant/lineage. Infections after vaccination were also reported on several occasions, but mostly associated with mild or no symptoms. Overall, findings suggest that infection- and vaccine-induced immunity would protect from severe illness, with the vaccine being effective against most VOCs.

5.
Front Med (Lausanne) ; 8: 733657, 2021.
Article in English | MEDLINE | ID: covidwho-1378195

ABSTRACT

Introduction: Detection of early metabolic changes in critically-ill coronavirus disease 2019 (COVID-19) patients under invasive mechanical ventilation (IMV) at the intensive care unit (ICU) could predict recovery patterns and help in disease management. Methods: Targeted metabolomics of serum samples from 39 COVID-19 patients under IMV in ICU was performed within 48 h of intubation and a week later. A generalized linear model (GLM) was used to identify, at both time points, metabolites and clinical traits that predict the length of stay (LOS) at ICU (short ≤ 14 days/long >14 days) as well as the duration under IMV. All models were initially trained on a set of randomly selected individuals and validated on the remaining individuals in the cohort. Further validation in recently published metabolomics data of COVID-19 severity was performed. Results: A model based on hypoxanthine and betaine measured at first time point was best at predicting whether a patient is likely to experience a short or long stay at ICU [area under curve (AUC) = 0.92]. A further model based on kynurenine, 3-methylhistidine, ornithine, p-cresol sulfate, and C24.0 sphingomyelin, measured 1 week later, accurately predicted the duration of IMV (Pearson correlation = 0.94). Both predictive models outperformed Acute Physiology and Chronic Health Evaluation II (APACHE II) scores and differentiated COVID-19 severity in published data. Conclusion: This study has identified specific metabolites that can predict in advance LOS and IMV, which could help in the management of COVID-19 cases at ICU.

6.
Infect Genet Evol ; 93: 104972, 2021 09.
Article in English | MEDLINE | ID: covidwho-1274364

ABSTRACT

Human influenza viruses are occasionally detected in the stools of influenza patients. OBJECTIVES: Here, we investigated the molecular and biological characteristics of intestinal influenza viruses and their potential role in virus transmission. METHODS: Fecal samples were first screened for the presence of influenza viral RNA using RT-qPCR. Positive fecal samples were subjected to cell culture. Isolated viruses were then sequenced using MiSeq platform. Replication kinetics and receptor binding affinity were also evaluated. RESULTS: Influenza RNA was detected in stool samples of 41% (36/87) of influenza A positive patients. Among the 36 stool samples subjected to viral isolation, 5 showed virus growth. Sequence analysis of isolated viruses revealed two distinct mutation patterns in fecal viruses. Set I viruses was able to replicate to higher titers in cell culture despite the limited number of mutations (6 mutations) compared to set II viruses (>10 mutations). Functional analysis of both sets revealed the ability to replicate efficiently in differentiated human bronchial cells. Receptor binding testing has also demonstrated their ability to bind α 2,3 and α 2,6 sialic acid receptors. CONCLUSION: The ability of fecal influenza viruses to replicate in intestinal cells and human 3D bronchial cells might suggest their possible contribution in virus transmission.


Subject(s)
Influenza A virus/genetics , Influenza, Human/epidemiology , Adolescent , Adult , Aged , Feces/virology , Humans , Influenza, Human/virology , Middle Aged , Prevalence , Qatar/epidemiology , Young Adult
7.
Microb Drug Resist ; 27(12): 1705-1725, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1254361

ABSTRACT

Objectives: Over the last decades, there has been a significant increase in antimicrobial prescribing and consumption associated with the development of patients' adverse events and antimicrobial resistance (AMR) to the point of becoming a global priority. This study aims at evaluating antibiotic prescribing during COVID-19 pandemic from November 2019 to December 2020. Materials and Methods: A systematic review was conducted primarily through the NCBI database, using PRISMA guidelines to identify relevant literature for the period between November 1, 2019 and December 19, 2020, using the keywords: COVID-19 OR SARS-Cov-2 AND antibiotics restricted to the English language excluding nonclinical articles. Five hundred twenty-seven titles were identified; all articles fulfilling the study criteria were included, 133 through the NCBI, and 8 through Google Scholar with a combined total of 141 studies. The patient's spectrum included all ages from neonates to elderly with all associated comorbidities, including immune suppression. Results: Of 28,093 patients included in the combined studies, 58.7% received antibiotics (16,490/28,093), ranging from 1.3% to 100% coverage. Antibiotics coverage was less in children (57%) than in adults with comorbidities (75%). Broad-spectrum antibiotics were prescribed presumptively without pathogen identifications, which might contribute to adverse outcomes. Conclusions: During the COVID-19 pandemic, there has been a significant and wide range of antibiotic prescribing in patients affected by the disease, particularly in adults with underlying comorbidities, despite the paucity of evidence of associated bacterial infections. The current practice might increase patients' immediate and long-term risks of adverse events, susceptibility to secondary infections as well as aggravating AMR.


Subject(s)
Anti-Bacterial Agents/therapeutic use , COVID-19/drug therapy , Adolescent , Adult , Aged , Aged, 80 and over , Anti-Bacterial Agents/administration & dosage , Child , Child, Preschool , Comorbidity , Drug Utilization , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Pandemics , SARS-CoV-2 , Young Adult
8.
Front Public Health ; 8: 573925, 2020.
Article in English | MEDLINE | ID: covidwho-1021920

ABSTRACT

Background: SARS-CoV-2 continues to claim hundreds of thousands of people's lives. It mostly affects the elderly and those with chronic illness but can also be fatal in younger age groups. This article is the first comprehensive analysis of the epidemiological and clinical outcomes of the travel-associated SARS-CoV-2 cases until April 19, 2020. Methods: Demographic and clinical data of travel-associated SARS-CoV-2 cases were collected for the period between January 16, 2020 and April 19, 2020. More than one hundred and eighty databases were searched, including the World Health Organization (WHO) database, countries' ministries websites, and official media sites. Demographic and clinical data were extracted and analyzed. Results: A total of 1,186 cases from 144 countries meeting the inclusion criteria were reported and included in the analysis. The mean age of the cases was 44 years, with a male to female ratio of 1.6:1. Travel-associated cases originated from more than 40 countries, with China, Italy, and Iran reporting the highest numbers at 208, 225, and 155, respectively. Clinical symptoms varied between patients, with some reporting symptoms during the flights (117 cases; 9.87%). A total of 312 (26.31%) cases were hospitalized, of which 50 cases (4.22%) were fatal. Conclusion: Major gaps exist in the epidemiology and clinical spectrum of the COVID-19 travel-associated cases due to a lack of reporting and sharing data of many counties. The identification and implementation of methodologies for measuring traveler's risk to coronavirus would help in minimizing the spread of the virus, especially in the next waves.


Subject(s)
COVID-19 , Demography , Infection Control , Travel , Adult , COVID-19/diagnosis , COVID-19/epidemiology , China/epidemiology , Female , Humans , Iran/epidemiology , Italy/epidemiology , Male , SARS-CoV-2/isolation & purification
9.
Viruses ; 13(1)2020 12 30.
Article in English | MEDLINE | ID: covidwho-1004762

ABSTRACT

In December 2019, the latest member of the coronavirus family, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in Wuhan, China, leading to the outbreak of an unusual viral pneumonia known as coronavirus disease 2019 (COVID-19). COVID-19 was then declared as a pandemic in March 2020 by the World Health Organization (WHO). The initial mortality rate of COVID-19 declared by WHO was 2%; however, this rate has increased to 3.4% as of 3 March 2020. People of all ages can be infected with SARS-CoV-2, but those aged 60 or above and those with underlying medical conditions are more prone to develop severe symptoms that may lead to death. Patients with severe infection usually experience a hyper pro-inflammatory immune reaction (i.e., cytokine storm) causing acute respiratory distress syndrome (ARDS), which has been shown to be the leading cause of death in COVID-19 patients. However, the factors associated with COVID-19 susceptibility, resistance and severity remain poorly understood. In this review, we thoroughly explore the correlation between various host, viral and environmental markers, and SARS-CoV-2 in terms of susceptibility and severity.


Subject(s)
COVID-19 , Disease Resistance , Disease Susceptibility , Severity of Illness Index , Angiotensin-Converting Enzyme 2/genetics , Blood Group Antigens , COVID-19/genetics , COVID-19/immunology , COVID-19/metabolism , Disease Outbreaks , Environment , Host-Pathogen Interactions , Humans , Metabolome , Microbiota , Middle Aged , Risk Factors , SARS-CoV-2 , Vitamins
10.
Front Cell Infect Microbiol ; 10: 575613, 2020.
Article in English | MEDLINE | ID: covidwho-890331

ABSTRACT

Background: The ongoing pandemic of SARS-COV-2 has already infected more than eight million people worldwide. The majority of COVID-19 patients either are asymptomatic or have mild symptoms. Yet, about 15% of the cases experience severe complications and require intensive care. Factors determining disease severity are not yet fully characterized. Aim: Here, we investigated the within-host virus diversity in COVID-19 patients with different clinical manifestations. Methods: We compared SARS-COV-2 genetic diversity in 19 mild and 27 severe cases. Viral RNA was extracted from nasopharyngeal samples and sequenced using the Illumina MiSeq platform. This was followed by deep-sequencing analyses of SARS-CoV-2 genomes at both consensus and sub-consensus sequence levels. Results: Consensus sequences of all viruses were very similar, showing more than 99.8% sequence identity regardless of the disease severity. However, the sub-consensus analysis revealed significant differences in within-host diversity between mild and severe cases. Patients with severe symptoms exhibited a significantly (p-value 0.001) higher number of variants in coding and non-coding regions compared to mild cases. Analysis also revealed higher prevalence of some variants among severe cases. Most importantly, severe cases exhibited significantly higher within-host diversity (mean = 13) compared to mild cases (mean = 6). Further, higher within-host diversity was observed in patients above the age of 60 compared to the younger age group. Conclusion: These observations provided evidence that within-host diversity might play a role in the development of severe disease outcomes in COVID-19 patients; however, further investigations are required to elucidate this association.


Subject(s)
Betacoronavirus/classification , Betacoronavirus/genetics , Genetic Variation/genetics , Genome, Viral/genetics , Severity of Illness Index , Adult , Aged , COVID-19 , Consensus Sequence/genetics , Coronavirus Infections/pathology , Female , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/pathology , RNA, Viral/genetics , Risk Factors , SARS-CoV-2 , Sequence Analysis, RNA , Young Adult
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