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Identification of sex-associated network patterns in Vaccine-Adverse Event Association Network in VAERS

BACKGROUND: Vaccines are one of the most important public health successes in last century. Besides effectiveness in reducing the morbidity and mortality from many infectious diseases, a successful vaccine program also requires a rigorous assessment on their safety. Due to the limitations of adverse...

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Autores principales: Zhang, Yuji, Wu, Puqiang, Luo, Yi, Tao, Cui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4541751/
https://www.ncbi.nlm.nih.gov/pubmed/26294955
http://dx.doi.org/10.1186/s13326-015-0032-2
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author Zhang, Yuji
Wu, Puqiang
Luo, Yi
Tao, Cui
author_facet Zhang, Yuji
Wu, Puqiang
Luo, Yi
Tao, Cui
author_sort Zhang, Yuji
collection PubMed
description BACKGROUND: Vaccines are one of the most important public health successes in last century. Besides effectiveness in reducing the morbidity and mortality from many infectious diseases, a successful vaccine program also requires a rigorous assessment on their safety. Due to the limitations of adverse event (AE) data from clinical trials and post-approval surveillance systems, novel computational approaches are needed to organize, visualize, and analyze such high-dimensional complex data. RESULTS: In this paper, we proposed a network-based approach to investigate the vaccine-AE association network from the Vaccine AE Reporting System (VAERS) data. Statistical summary was calculated using the VAERS raw data and represented in the Resource Description Framework (RDF). The RDF graph was leveraged for network analysis. Specifically, we compared network properties of (1) vaccine - adverse event association network based on reports collected over a 23 year period as well as each year; and (2) sex-specific vaccine-adverse event association network. We observed that (1) network diameter and average path length don’t change dramatically over a 23-year period, while the average node degree of these networks changes due to the different number of reports during different periods of time; (2) vaccine - adverse event associations derived from different sexes show sex-associated patterns in sex-specific vaccine-AE association networks. CONCLUSIONS: We have developed a network-based approach to investigate the vaccine-AE association network from the VAERS data. To our knowledge, this is the first time that a network-based approach was used to identify sex-specific association patterns in a spontaneous reporting system database. Due to unique limitations of such passive surveillance systems, our proposed network-based approaches have the potential to summarize and analyze the associations in passive surveillance systems by (1) identifying nodes of importance, irrespective of whether they are disproportionally reported; (2) providing guidance on sex-specific recommendations in personalized vaccinology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13326-015-0032-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-45417512015-08-21 Identification of sex-associated network patterns in Vaccine-Adverse Event Association Network in VAERS Zhang, Yuji Wu, Puqiang Luo, Yi Tao, Cui J Biomed Semantics Research Article BACKGROUND: Vaccines are one of the most important public health successes in last century. Besides effectiveness in reducing the morbidity and mortality from many infectious diseases, a successful vaccine program also requires a rigorous assessment on their safety. Due to the limitations of adverse event (AE) data from clinical trials and post-approval surveillance systems, novel computational approaches are needed to organize, visualize, and analyze such high-dimensional complex data. RESULTS: In this paper, we proposed a network-based approach to investigate the vaccine-AE association network from the Vaccine AE Reporting System (VAERS) data. Statistical summary was calculated using the VAERS raw data and represented in the Resource Description Framework (RDF). The RDF graph was leveraged for network analysis. Specifically, we compared network properties of (1) vaccine - adverse event association network based on reports collected over a 23 year period as well as each year; and (2) sex-specific vaccine-adverse event association network. We observed that (1) network diameter and average path length don’t change dramatically over a 23-year period, while the average node degree of these networks changes due to the different number of reports during different periods of time; (2) vaccine - adverse event associations derived from different sexes show sex-associated patterns in sex-specific vaccine-AE association networks. CONCLUSIONS: We have developed a network-based approach to investigate the vaccine-AE association network from the VAERS data. To our knowledge, this is the first time that a network-based approach was used to identify sex-specific association patterns in a spontaneous reporting system database. Due to unique limitations of such passive surveillance systems, our proposed network-based approaches have the potential to summarize and analyze the associations in passive surveillance systems by (1) identifying nodes of importance, irrespective of whether they are disproportionally reported; (2) providing guidance on sex-specific recommendations in personalized vaccinology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13326-015-0032-2) contains supplementary material, which is available to authorized users. BioMed Central 2015-08-19 /pmc/articles/PMC4541751/ /pubmed/26294955 http://dx.doi.org/10.1186/s13326-015-0032-2 Text en © Zhang et al. 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Zhang, Yuji
Wu, Puqiang
Luo, Yi
Tao, Cui
Identification of sex-associated network patterns in Vaccine-Adverse Event Association Network in VAERS
title Identification of sex-associated network patterns in Vaccine-Adverse Event Association Network in VAERS
title_full Identification of sex-associated network patterns in Vaccine-Adverse Event Association Network in VAERS
title_fullStr Identification of sex-associated network patterns in Vaccine-Adverse Event Association Network in VAERS
title_full_unstemmed Identification of sex-associated network patterns in Vaccine-Adverse Event Association Network in VAERS
title_short Identification of sex-associated network patterns in Vaccine-Adverse Event Association Network in VAERS
title_sort identification of sex-associated network patterns in vaccine-adverse event association network in vaers
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4541751/
https://www.ncbi.nlm.nih.gov/pubmed/26294955
http://dx.doi.org/10.1186/s13326-015-0032-2
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