Cov19VaxKB: A Web-based Integrative COVID-19 Vaccine Knowledge Base

Systematic collection, annotation, and pattern analysis of viral vaccines in the VIOLIN vaccine knowledgebase

Background

Viral vaccines have been proven significant in protecting us against viral diseases such as COVID-19. To better understand and design viral vaccines, it is critical to systematically collect, annotate, and analyse various viral vaccines and identify enriched patterns from these viral vaccines.

Methods

We systematically collected experimentally verified viral vaccines from the literature, manually annotated, and stored the information in the VIOLIN vaccine database. The annotated information included basic vaccine names, pathogens and diseases, vaccine components, vaccine formulations, and their induced host responses. Enriched patterns were identified from our systematical analysis of the viral vaccines and vaccine antigens.

Results

A total of 2,847 viral vaccines against 95 viral species (including 72 RNA viral species and 23 DNA viral species) were collected, manually annotated, and stored in the VIOLIN vaccine database. These viral vaccines used 542 vaccine antigens. A taxonomical analysis found various DNA and RNA viruses covered by the viral vaccines. These vaccines target different viral life cycle stages (e.g., viral entry, assembly, exit, and immune evasion) as identified in top ranked human, animal vaccines, and HPV vaccines. The vaccine antigen proteins also show up in different virion locations in viruses such as HRSV vaccines. Both structural and non-structural viral proteins have been used for viral vaccine development. Protective vaccine antigens tend to have a protegenicity score of >85% based on the Vaxign-ML calculation, which measures predicted suitability for vaccine use. While predicted adhesins still have significantly higher chances of being protective antigens, only 21.42% of protective viral vaccine antigens were predicted to be adhesins. Furthermore, our Gene Ontology (GO) enrichment analysis using a customized Fisher's exact test identified many enriched patterns such as viral entry into the host cell, DNA/RNA/ATP/ion binding, and suppression of host type 1 interferon-mediated signaling pathway. The viral vaccines and their associated entities and relations are ontologically modeled and represented in the Vaccine Ontology (VO). A VIOLIN web interface was developed to support user friendly queries of viral vaccines.

Discussion

Viral vaccines were systematically collected and annotated in the VIOLIN vaccine knowledgebase, and the analysis of these viral vaccines identified many insightful patterns.

Association of Cardiovascular Events with COVID-19 Vaccines Using Vaccine Adverse Event Reporting System (VAERS): A Retrospective Study

BACKGROUND

COVID-19 vaccines have played a crucial role in reducing the burden of the global pandemic. However, recent case reports have indicated the association of the COVID- 19 vaccines with cardiovascular events but the exact association is unclear so far.

OBJECTIVE

Therefore, the objective of the current study is to find out the association of cardiovascular events with COVID-19 vaccines.

METHODS

The COVID-19 Vaccine Knowledge Base (Cov19VaxKB) tool was used to query the Vaccine Adverse Event Reporting System (VAERS) database. The proportional reporting ratio [PRR (≥2)] with associated chi-squared value (>4), and the number of cases > 0.2% of total reports, was used to assess the association of COVID-19 vaccines with cardiovascular events.

RESULTS

A total of 33,754 cases of cardiovascular events associated with COVID-19 vaccines were found in the Cov19VaxKB tool. The cases were observed in different age groups (18-64, and 65 years and above) and gender. The disproportionality measures indicate a statistically significant association between cardiovascular events and COVID-19 vaccines.

CONCLUSION

The current study identified a signal of various cardiovascular events with the COVID-19 vaccines. However, further causality assessment is required to confirm the association.

Applying the digital data and the bioinformatics tools in SARS-CoV-2 research

Bioinformatics has been playing a crucial role in the scientific progress to fight against the pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The advances in novel algorithms, mega data technology, artificial intelligence and deep learning assisted the development of novel bioinformatics tools to analyze daily increasing SARS-CoV-2 data in the past years. These tools were applied in genomic analyses, evolutionary tracking, epidemiological analyses, protein structure interpretation, studies in virus-host interaction and clinical performance. To promote the in-silico analysis in the future, we conducted a review which summarized the databases, web services and software applied in SARS-CoV-2 research. Those digital resources applied in SARS-CoV-2 research may also potentially contribute to the research in other coronavirus and non-coronavirus viruses.

A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology

BACKGROUND

The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the development of the community-based Coronavirus Infectious Disease Ontology (CIDO) in early 2020.

RESULTS

As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment.

CONCLUSION

CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications.

Profiling COVID-19 Vaccine Adverse Events by Statistical and Ontological Analysis of VAERS Case Reports

Since the beginning of the COVID-19 pandemic, vaccines have been developed to mitigate the spread of SARS-CoV-2, the virus that causes COVID-19. These vaccines have been effective in reducing the rate and severity of COVID-19 infection but also have been associated with various adverse events (AEs). In this study, data from the Vaccine Adverse Event Reporting System (VAERS) was queried and analyzed via the Cov19VaxKB vaccine safety statistical analysis tool to identify statistically significant (i.e., enriched) AEs for the three currently FDA-authorized or approved COVID-19 vaccines. An ontology-based classification and literature review were conducted for these enriched AEs. Using VAERS data as of 31 December 2021, 96 AEs were found to be statistically significantly associated with the Pfizer-BioNTech, Moderna, and/or Janssen COVID-19 vaccines. The Janssen COVID-19 vaccine had a higher crude reporting rate of AEs compared to the Moderna and Pfizer COVID-19 vaccines. Females appeared to have a higher case report frequency for top adverse events compared to males. Using the Ontology of Adverse Event (OAE), these 96 adverse events were classified to different categories such as behavioral and neurological AEs, cardiovascular AEs, female reproductive system AEs, and immune system AEs. Further statistical comparison between different ages, doses, and sexes was also performed for three notable AEs: myocarditis, GBS, and thrombosis. The Pfizer vaccine was found to have a closer association with myocarditis than the other two COVID-19 vaccines in VAERS, while the Janssen vaccine was more likely to be associated with thrombosis and GBS AEs. To support standard AE representation and study, we have also modeled and classified the newly identified thrombosis with thrombocytopenia syndrome (TTS) AE and its subclasses in the OAE by incorporating the Brighton Collaboration definition. Notably, severe COVID-19 vaccine AEs (including myocarditis, GBS, and TTS) rarely occur in comparison to the large number of COVID-19 vaccinations administered in the United States, affirming the overall safety of these COVID-19 vaccines.

SARS-CoV-2: vaccinology and emerging therapeutics; challenges and future developments

As SARS-CoV-2 emerge, variants such as Omicron (B.1.1.529), Delta (B.1.617.2), and those from the United Kingdom (B.1.1.7), South Africa (B.1.351), Brazil (P.1) and India (B.1.6.17 lineage) have raised concerns of the reduced neutralising ability of antibodies and increased ability to evade the current six approved COVID-19 vaccine candidates. This viewpoint advocates for countries to conduct prior efficacy studies before they embark on mass vaccination and addresses the role of nanoparticles as carrier vehicles for these vaccines with a view to explore the present challenges and forge a path for a stronger and more viable future for the development of vaccines for SARS-CoV-2 and future pandemics. We also look at the emerging prophylactics and therapeutics in the light of ongoing cases of severe and critical COVID-19.