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Ontology-based combinatorial comparative analysis of adverse events associated with killed and live influenza vaccines.

ABSTRACT: Vaccine adverse events (VAEs) are adverse bodily changes occurring after vaccination. Understanding the adverse event (AE) profiles is a crucial step to identify serious AEs. Two different types of seasonal influenza vaccines have been used on the market: trivalent (killed) inactivated influenza vaccine (TIV) and trivalent live attenuated influenza vaccine (LAIV). Different adverse event profiles induced by these two groups of seasonal influenza vaccines were studied based on the data drawn from the CDC Vaccine Adverse Event Report System (VAERS). Extracted from VAERS were 37,621 AE reports for four TIVs (Afluria, Fluarix, Fluvirin, and Fluzone) and 3,707 AE reports for the only LAIV (FluMist). The AE report data were analyzed by a novel combinatorial, ontology-based detection of AE method (CODAE). CODAE detects AEs using Proportional Reporting Ratio (PRR), Chi-square significance test, and base level filtration, and groups identified AEs by ontology-based hierarchical classification. In total, 48 TIV-enriched and 68 LAIV-enriched AEs were identified (PRR>2, Chi-square score >4, and the number of cases >0.2% of total reports). These AE terms were classified using the Ontology of Adverse Events (OAE), MedDRA, and SNOMED-CT. The OAE method provided better classification results than the two other methods. Thirteen out of 48 TIV-enriched AEs were related to neurological and muscular processing such as paralysis, movement disorders, and muscular weakness. In contrast, 15 out of 68 LAIV-enriched AEs were associated with inflammatory response and respiratory system disorders. There were evidences of two severe adverse events (Guillain-Barre Syndrome and paralysis) present in TIV. Although these severe adverse events were at low incidence rate, they were found to be more significantly enriched in TIV-vaccinated patients than LAIV-vaccinated patients. Therefore, our novel combinatorial bioinformatics analysis discovered that LAIV had lower chance of inducing these two severe adverse events than TIV. In addition, our meta-analysis found that all previously reported positive correlation between GBS and influenza vaccine immunization were based on trivalent influenza vaccines instead of monovalent influenza vaccines.

SUBMITTER: Sarntivijai S

PROVIDER: S-EPMC3509157 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Ontology-based combinatorial comparative analysis of adverse events associated with killed and live influenza vaccines.

Sarntivijai Sirarat S Xiang Zuoshuang Z Shedden Kerby A KA Markel Howard H Omenn Gilbert S GS Athey Brian D BD He Yongqun Y

PloS one 20121128 11

Vaccine adverse events (VAEs) are adverse bodily changes occurring after vaccination. Understanding the adverse event (AE) profiles is a crucial step to identify serious AEs. Two different types of seasonal influenza vaccines have been used on the market: trivalent (killed) inactivated influenza vaccine (TIV) and trivalent live attenuated influenza vaccine (LAIV). Different adverse event profiles induced by these two groups of seasonal influenza vaccines were studied based on the data drawn from ...[more]

PMID: 23209624

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Project description:BackgroundA medical intervention is a medical procedure or application intended to relieve or prevent illness or injury. Examples of medical interventions include vaccination and drug administration. After a medical intervention, adverse events (AEs) may occur which lie outside the intended consequences of the intervention. The representation and analysis of AEs are critical to the improvement of public health.DescriptionThe Ontology of Adverse Events (OAE), previously named Adverse Event Ontology (AEO), is a community-driven ontology developed to standardize and integrate data relating to AEs arising subsequent to medical interventions, as well as to support computer-assisted reasoning. OAE has over 3,000 terms with unique identifiers, including terms imported from existing ontologies and more than 1,800 OAE-specific terms. In OAE, the term 'adverse event' denotes a pathological bodily process in a patient that occurs after a medical intervention. Causal adverse events are defined by OAE as those events that are causal consequences of a medical intervention. OAE represents various adverse events based on patient anatomic regions and clinical outcomes, including symptoms, signs, and abnormal processes. OAE has been used in the analysis of several different sorts of vaccine and drug adverse event data. For example, using the data extracted from the Vaccine Adverse Event Reporting System (VAERS), OAE was used to analyse vaccine adverse events associated with the administrations of different types of influenza vaccines. OAE has also been used to represent and classify the vaccine adverse events cited in package inserts of FDA-licensed human vaccines in the USA.ConclusionOAE is a biomedical ontology that logically defines and classifies various adverse events occurring after medical interventions. OAE has successfully been applied in several adverse event studies. The OAE ontological framework provides a platform for systematic representation and analysis of adverse events and of the factors (e.g., vaccinee age) important for determining their clinical outcomes.

Project description:Nonstructural protein 1 (NS1) of influenza virus is a key virulence element with multifunctional roles in virus replication and a potent antagonist of host immune response. Deletion of NS1 (DelNS1) would create a safer and more extensively immunogenic live attenuated influenza virus (LAIV) vaccine. However, DelNS1 viruses are very difficult to grow in regular vaccine-producing systems, which has hampered the application of DelNS1 LAIV vaccines in humans. We have developed two master backbones of deleted-NS1 (DelNS1) viral genomes from influenza A or B viruses which contain novel adaptive mutations to support DelNS1-LAIV replication. These DelNS1-LAIVs are highly attenuated in human cells in vitro and nonpathogenic in mice but replicate well in vaccine-producing cells. Both influenza A and influenza B DelNS1 LAIVs grow better at 33°C than at 37 to 39°C. Vaccination with DelNS1 LAIV performed once is enough to provide potent protection against lethal challenge with homologous virus and strong long-lasting cross protection against heterosubtypic or antigenically distantly related influenza viruses in mice. Mechanistic investigations revealed that DelNS1-LAIVs induce cross protective neutralizing antibody and CD8+ and CD4+ T cell immunities. Importantly, it has been shown that DelNS1-LAIV can be used to enhance specific anti-influenza immunity through expression of additional antigens from the deleted-NS1 site. Generation of DelNS1 viruses which are nonpathogenic and able to grow in vaccine-producing systems is an important strategy for making highly immunogenic LAIV vaccines that induce broad cross protective immunity against seasonal and emerging influenza.IMPORTANCE Current seasonal influenza vaccines are suboptimal and low in immunogenicity and do not provide long-lasting immunity and cross protection against influenza virus strains that have antigenically drifted. More-effective influenza vaccines which can induce both humoral immunity and T cell immunity are needed. The NS1 protein of influenza virus is a virulence element and the critical factor for regulation of the host immune response during virus infection. Deletion of the NS1 protein is a strategy to make an optimal LAIV vaccine. However, DelNS1 viruses are very difficult to grow in regular vaccine-producing systems, hampering the application of DelNS1 LAIV vaccines in humans. We have generated a panel of both influenza A and influenza B DelNS1 LAIVs which are able to grow in regular vaccine-producing cells. These DelNS1 LAIV vaccines are completely nonpathogenic, exhibit potent and long-lasting immunity, and can be used to express extra viral antigen to induce cross protective immunity against seasonal and emerging influenza.

Project description:Influenza virus still represents a considerable threat to global public health, despite the advances in the development and wide use of influenza vaccines. Vaccination with traditional inactivate influenza vaccines (IIV) or live-attenuated influenza vaccines (LAIV) remains the main strategy in the control of annual seasonal epidemics, but it does not offer protection against new influenza viruses with pandemic potential, those that have shifted. Moreover, the continual antigenic drift of seasonal circulating influenza viruses, causing an antigenic mismatch that requires yearly reformulation of seasonal influenza vaccines, seriously compromises vaccine efficacy. Therefore, the quick optimization of vaccine production for seasonal influenza and the development of new vaccine approaches for pandemic viruses is still a challenge for the prevention of influenza infections. Moreover, recent reports have questioned the effectiveness of the current LAIV because of limited protection, mainly against the influenza A virus (IAV) component of the vaccine. Although the reasons for the poor protection efficacy of the LAIV have not yet been elucidated, researchers are encouraged to develop new vaccination approaches that overcome the limitations that are associated with the current LAIV. The discovery and implementation of plasmid-based reverse genetics has been a key advance in the rapid generation of recombinant attenuated influenza viruses that can be used for the development of new and most effective LAIV. In this review, we provide an update regarding the progress that has been made during the last five years in the development of new LAIV and the innovative ways that are being explored as alternatives to the currently licensed LAIV. The safety, immunogenicity, and protection efficacy profile of these new LAIVs reveal their possible implementation in combating influenza infections. However, efforts by vaccine companies and government agencies will be needed for controlled testing and approving, respectively, these new vaccine methodologies for the control of influenza infections.

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Ontology-based combinatorial comparative analysis of adverse events associated with killed and live influenza vaccines.

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Ontology-based combinatorial comparative analysis of adverse events associated with killed and live influenza vaccines.

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